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| I0407 15:14:50.542440 1004 solver.cpp:280] Solving | |
| I0407 15:14:50.542451 1004 solver.cpp:281] Learning Rate Policy: poly | |
| I0407 15:14:50.601984 1004 solver.cpp:229] Iteration 0, loss = 4.3042 | |
| I0407 15:14:50.602022 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 15:14:50.602041 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:14:50.602053 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:14:50.602068 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 15:14:50.602082 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0 | |
| I0407 15:14:50.602092 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0 | |
| I0407 15:14:50.602120 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0 | |
| I0407 15:14:50.602133 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0 | |
| I0407 15:14:50.602145 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0 | |
| I0407 15:14:50.602156 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0 | |
| I0407 15:14:50.602167 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 0 | |
| I0407 15:14:50.602179 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 0.0625 | |
| I0407 15:14:50.602191 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 0 | |
| I0407 15:14:50.602202 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 0 | |
| I0407 15:14:50.602215 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 0 | |
| I0407 15:14:50.602226 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 0 | |
| I0407 15:14:50.602236 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 0 | |
| I0407 15:14:50.602248 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 0 | |
| I0407 15:14:50.602260 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 0 | |
| I0407 15:14:50.602272 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 0 | |
| I0407 15:14:50.602283 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 0 | |
| I0407 15:14:50.602294 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 0 | |
| I0407 15:14:50.602313 1004 solver.cpp:245] Train net output #22: loss/loss01 = 4.30402 (* 0.0454545 = 0.195637 loss) | |
| I0407 15:14:50.602327 1004 solver.cpp:245] Train net output #23: loss/loss02 = 4.30418 (* 0.0454545 = 0.195644 loss) | |
| I0407 15:14:50.602341 1004 solver.cpp:245] Train net output #24: loss/loss03 = 4.30405 (* 0.0454545 = 0.195639 loss) | |
| I0407 15:14:50.602355 1004 solver.cpp:245] Train net output #25: loss/loss04 = 4.30409 (* 0.0454545 = 0.195641 loss) | |
| I0407 15:14:50.602368 1004 solver.cpp:245] Train net output #26: loss/loss05 = 4.30427 (* 0.0454545 = 0.195648 loss) | |
| I0407 15:14:50.602385 1004 solver.cpp:245] Train net output #27: loss/loss06 = 4.30422 (* 0.0454545 = 0.195646 loss) | |
| I0407 15:14:50.602399 1004 solver.cpp:245] Train net output #28: loss/loss07 = 4.30442 (* 0.0454545 = 0.195655 loss) | |
| I0407 15:14:50.602413 1004 solver.cpp:245] Train net output #29: loss/loss08 = 4.30441 (* 0.0454545 = 0.195655 loss) | |
| I0407 15:14:50.602427 1004 solver.cpp:245] Train net output #30: loss/loss09 = 4.30435 (* 0.0454545 = 0.195652 loss) | |
| I0407 15:14:50.602440 1004 solver.cpp:245] Train net output #31: loss/loss10 = 4.30442 (* 0.0454545 = 0.195655 loss) | |
| I0407 15:14:50.602454 1004 solver.cpp:245] Train net output #32: loss/loss11 = 4.30405 (* 0.0454545 = 0.195639 loss) | |
| I0407 15:14:50.602468 1004 solver.cpp:245] Train net output #33: loss/loss12 = 4.3036 (* 0.0454545 = 0.195618 loss) | |
| I0407 15:14:50.602481 1004 solver.cpp:245] Train net output #34: loss/loss13 = 4.30382 (* 0.0454545 = 0.195628 loss) | |
| I0407 15:14:50.602495 1004 solver.cpp:245] Train net output #35: loss/loss14 = 4.30447 (* 0.0454545 = 0.195658 loss) | |
| I0407 15:14:50.602509 1004 solver.cpp:245] Train net output #36: loss/loss15 = 4.30378 (* 0.0454545 = 0.195626 loss) | |
| I0407 15:14:50.602522 1004 solver.cpp:245] Train net output #37: loss/loss16 = 4.30419 (* 0.0454545 = 0.195645 loss) | |
| I0407 15:14:50.602535 1004 solver.cpp:245] Train net output #38: loss/loss17 = 4.30434 (* 0.0454545 = 0.195652 loss) | |
| I0407 15:14:50.602550 1004 solver.cpp:245] Train net output #39: loss/loss18 = 4.30449 (* 0.0454545 = 0.195659 loss) | |
| I0407 15:14:50.602563 1004 solver.cpp:245] Train net output #40: loss/loss19 = 4.30435 (* 0.0454545 = 0.195652 loss) | |
| I0407 15:14:50.602576 1004 solver.cpp:245] Train net output #41: loss/loss20 = 4.30444 (* 0.0454545 = 0.195656 loss) | |
| I0407 15:14:50.602591 1004 solver.cpp:245] Train net output #42: loss/loss21 = 4.30406 (* 0.0454545 = 0.195639 loss) | |
| I0407 15:14:50.602603 1004 solver.cpp:245] Train net output #43: loss/loss22 = 4.30444 (* 0.0454545 = 0.195656 loss) | |
| I0407 15:14:50.602625 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:14:50.602638 1004 solver.cpp:245] Train net output #45: total_confidence = 7.77861e-42 | |
| I0407 15:14:50.602663 1004 sgd_solver.cpp:106] Iteration 0, lr = 0.001 | |
| I0407 15:15:28.466101 1004 solver.cpp:229] Iteration 500, loss = 4.15622 | |
| I0407 15:15:28.466258 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 15:15:28.466277 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:15:28.466290 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:15:28.466305 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 15:15:28.466316 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 15:15:28.466328 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5 | |
| I0407 15:15:28.466341 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 15:15:28.466353 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 15:15:28.466366 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:15:28.466377 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:15:28.466388 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:15:28.466400 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:15:28.466413 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:15:28.466424 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:15:28.466436 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:15:28.466447 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:15:28.466459 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:15:28.466471 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:15:28.466482 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:15:28.466495 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:15:28.466506 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:15:28.466517 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:15:28.466532 1004 solver.cpp:245] Train net output #22: loss/loss01 = 4.29894 (* 0.0454545 = 0.195406 loss) | |
| I0407 15:15:28.466547 1004 solver.cpp:245] Train net output #23: loss/loss02 = 4.30041 (* 0.0454545 = 0.195473 loss) | |
| I0407 15:15:28.466562 1004 solver.cpp:245] Train net output #24: loss/loss03 = 4.3008 (* 0.0454545 = 0.195491 loss) | |
| I0407 15:15:28.466575 1004 solver.cpp:245] Train net output #25: loss/loss04 = 4.29867 (* 0.0454545 = 0.195394 loss) | |
| I0407 15:15:28.466589 1004 solver.cpp:245] Train net output #26: loss/loss05 = 4.28876 (* 0.0454545 = 0.194944 loss) | |
| I0407 15:15:28.466603 1004 solver.cpp:245] Train net output #27: loss/loss06 = 4.22321 (* 0.0454545 = 0.191964 loss) | |
| I0407 15:15:28.466617 1004 solver.cpp:245] Train net output #28: loss/loss07 = 4.07307 (* 0.0454545 = 0.185139 loss) | |
| I0407 15:15:28.466631 1004 solver.cpp:245] Train net output #29: loss/loss08 = 3.94756 (* 0.0454545 = 0.179434 loss) | |
| I0407 15:15:28.466645 1004 solver.cpp:245] Train net output #30: loss/loss09 = 3.89266 (* 0.0454545 = 0.176939 loss) | |
| I0407 15:15:28.466658 1004 solver.cpp:245] Train net output #31: loss/loss10 = 3.88092 (* 0.0454545 = 0.176406 loss) | |
| I0407 15:15:28.466673 1004 solver.cpp:245] Train net output #32: loss/loss11 = 3.872 (* 0.0454545 = 0.176 loss) | |
| I0407 15:15:28.466687 1004 solver.cpp:245] Train net output #33: loss/loss12 = 3.86888 (* 0.0454545 = 0.175858 loss) | |
| I0407 15:15:28.466701 1004 solver.cpp:245] Train net output #34: loss/loss13 = 3.86966 (* 0.0454545 = 0.175894 loss) | |
| I0407 15:15:28.466716 1004 solver.cpp:245] Train net output #35: loss/loss14 = 3.87604 (* 0.0454545 = 0.176184 loss) | |
| I0407 15:15:28.466729 1004 solver.cpp:245] Train net output #36: loss/loss15 = 3.86969 (* 0.0454545 = 0.175895 loss) | |
| I0407 15:15:28.466743 1004 solver.cpp:245] Train net output #37: loss/loss16 = 3.87173 (* 0.0454545 = 0.175988 loss) | |
| I0407 15:15:28.466758 1004 solver.cpp:245] Train net output #38: loss/loss17 = 3.87168 (* 0.0454545 = 0.175985 loss) | |
| I0407 15:15:28.466771 1004 solver.cpp:245] Train net output #39: loss/loss18 = 3.87305 (* 0.0454545 = 0.176048 loss) | |
| I0407 15:15:28.466800 1004 solver.cpp:245] Train net output #40: loss/loss19 = 3.87164 (* 0.0454545 = 0.175984 loss) | |
| I0407 15:15:28.466815 1004 solver.cpp:245] Train net output #41: loss/loss20 = 3.87493 (* 0.0454545 = 0.176133 loss) | |
| I0407 15:15:28.466830 1004 solver.cpp:245] Train net output #42: loss/loss21 = 3.87095 (* 0.0454545 = 0.175952 loss) | |
| I0407 15:15:28.466843 1004 solver.cpp:245] Train net output #43: loss/loss22 = 3.87381 (* 0.0454545 = 0.176082 loss) | |
| I0407 15:15:28.466856 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:15:28.466867 1004 solver.cpp:245] Train net output #45: total_confidence = 8.47256e-39 | |
| I0407 15:15:28.466881 1004 sgd_solver.cpp:106] Iteration 500, lr = 0.000999 | |
| I0407 15:16:06.256582 1004 solver.cpp:229] Iteration 1000, loss = 3.73107 | |
| I0407 15:16:06.256698 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 15:16:06.256718 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:16:06.256731 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 15:16:06.256744 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 15:16:06.256757 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0 | |
| I0407 15:16:06.256767 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0 | |
| I0407 15:16:06.256779 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.625 | |
| I0407 15:16:06.256791 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 15:16:06.256803 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:16:06.256815 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:16:06.256827 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:16:06.256839 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:16:06.256850 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:16:06.256862 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:16:06.256873 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:16:06.256886 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:16:06.256896 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:16:06.256908 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:16:06.256921 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:16:06.256932 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:16:06.256944 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:16:06.256956 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:16:06.256971 1004 solver.cpp:245] Train net output #22: loss/loss01 = 4.00873 (* 0.0454545 = 0.182215 loss) | |
| I0407 15:16:06.256985 1004 solver.cpp:245] Train net output #23: loss/loss02 = 4.35265 (* 0.0454545 = 0.197848 loss) | |
| I0407 15:16:06.256999 1004 solver.cpp:245] Train net output #24: loss/loss03 = 4.25774 (* 0.0454545 = 0.193534 loss) | |
| I0407 15:16:06.257014 1004 solver.cpp:245] Train net output #25: loss/loss04 = 4.22139 (* 0.0454545 = 0.191882 loss) | |
| I0407 15:16:06.257027 1004 solver.cpp:245] Train net output #26: loss/loss05 = 4.39398 (* 0.0454545 = 0.199727 loss) | |
| I0407 15:16:06.257041 1004 solver.cpp:245] Train net output #27: loss/loss06 = 4.23028 (* 0.0454545 = 0.192285 loss) | |
| I0407 15:16:06.257055 1004 solver.cpp:245] Train net output #28: loss/loss07 = 3.2598 (* 0.0454545 = 0.148173 loss) | |
| I0407 15:16:06.257069 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.4248 (* 0.0454545 = 0.0647634 loss) | |
| I0407 15:16:06.257087 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.534303 (* 0.0454545 = 0.0242865 loss) | |
| I0407 15:16:06.257102 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.000726271 (* 0.0454545 = 3.30123e-05 loss) | |
| I0407 15:16:06.257117 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000106567 (* 0.0454545 = 4.84393e-06 loss) | |
| I0407 15:16:06.257131 1004 solver.cpp:245] Train net output #33: loss/loss12 = 3.35888e-05 (* 0.0454545 = 1.52676e-06 loss) | |
| I0407 15:16:06.257145 1004 solver.cpp:245] Train net output #34: loss/loss13 = 5.35354e-05 (* 0.0454545 = 2.43343e-06 loss) | |
| I0407 15:16:06.257159 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00019694 (* 0.0454545 = 8.95183e-06 loss) | |
| I0407 15:16:06.257174 1004 solver.cpp:245] Train net output #36: loss/loss15 = 5.2357e-05 (* 0.0454545 = 2.37986e-06 loss) | |
| I0407 15:16:06.257189 1004 solver.cpp:245] Train net output #37: loss/loss16 = 8.4608e-05 (* 0.0454545 = 3.84582e-06 loss) | |
| I0407 15:16:06.257202 1004 solver.cpp:245] Train net output #38: loss/loss17 = 6.8814e-05 (* 0.0454545 = 3.12791e-06 loss) | |
| I0407 15:16:06.257230 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000118135 (* 0.0454545 = 5.36978e-06 loss) | |
| I0407 15:16:06.257246 1004 solver.cpp:245] Train net output #40: loss/loss19 = 9.38366e-05 (* 0.0454545 = 4.2653e-06 loss) | |
| I0407 15:16:06.257259 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000129618 (* 0.0454545 = 5.89173e-06 loss) | |
| I0407 15:16:06.257274 1004 solver.cpp:245] Train net output #42: loss/loss21 = 7.36929e-05 (* 0.0454545 = 3.34968e-06 loss) | |
| I0407 15:16:06.257287 1004 solver.cpp:245] Train net output #43: loss/loss22 = 7.96104e-05 (* 0.0454545 = 3.61866e-06 loss) | |
| I0407 15:16:06.257300 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:16:06.257311 1004 solver.cpp:245] Train net output #45: total_confidence = 1.62451e-09 | |
| I0407 15:16:06.257325 1004 sgd_solver.cpp:106] Iteration 1000, lr = 0.000998 | |
| I0407 15:16:43.939045 1004 solver.cpp:229] Iteration 1500, loss = 1.17895 | |
| I0407 15:16:43.939137 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:16:43.939157 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:16:43.939168 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 15:16:43.939182 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 15:16:43.939193 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 15:16:43.939205 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 15:16:43.939218 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 15:16:43.939229 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 15:16:43.939241 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:16:43.939256 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 15:16:43.939270 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:16:43.939281 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:16:43.939293 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:16:43.939306 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:16:43.939328 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:16:43.939344 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:16:43.939355 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:16:43.939368 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:16:43.939378 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:16:43.939390 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:16:43.939401 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:16:43.939414 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:16:43.939429 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.92654 (* 0.0454545 = 0.178479 loss) | |
| I0407 15:16:43.939445 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.83849 (* 0.0454545 = 0.174477 loss) | |
| I0407 15:16:43.939465 1004 solver.cpp:245] Train net output #24: loss/loss03 = 4.07168 (* 0.0454545 = 0.185076 loss) | |
| I0407 15:16:43.939479 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.90695 (* 0.0454545 = 0.177589 loss) | |
| I0407 15:16:43.939493 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.51167 (* 0.0454545 = 0.159622 loss) | |
| I0407 15:16:43.939507 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.31569 (* 0.0454545 = 0.150713 loss) | |
| I0407 15:16:43.939522 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.94479 (* 0.0454545 = 0.0883996 loss) | |
| I0407 15:16:43.939535 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.37529 (* 0.0454545 = 0.0625131 loss) | |
| I0407 15:16:43.939549 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.532317 (* 0.0454545 = 0.0241962 loss) | |
| I0407 15:16:43.939563 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.508725 (* 0.0454545 = 0.0231239 loss) | |
| I0407 15:16:43.939579 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.00161178 (* 0.0454545 = 7.32626e-05 loss) | |
| I0407 15:16:43.939594 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00114199 (* 0.0454545 = 5.19085e-05 loss) | |
| I0407 15:16:43.939607 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.00111889 (* 0.0454545 = 5.08585e-05 loss) | |
| I0407 15:16:43.939621 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00179907 (* 0.0454545 = 8.1776e-05 loss) | |
| I0407 15:16:43.939636 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.00129373 (* 0.0454545 = 5.8806e-05 loss) | |
| I0407 15:16:43.939651 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.00161798 (* 0.0454545 = 7.35445e-05 loss) | |
| I0407 15:16:43.939664 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.00153596 (* 0.0454545 = 6.98165e-05 loss) | |
| I0407 15:16:43.939697 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.00171755 (* 0.0454545 = 7.80703e-05 loss) | |
| I0407 15:16:43.939713 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.0016039 (* 0.0454545 = 7.29048e-05 loss) | |
| I0407 15:16:43.939726 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.00159063 (* 0.0454545 = 7.23011e-05 loss) | |
| I0407 15:16:43.939740 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.0016175 (* 0.0454545 = 7.35227e-05 loss) | |
| I0407 15:16:43.939754 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00152259 (* 0.0454545 = 6.92085e-05 loss) | |
| I0407 15:16:43.939767 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:16:43.939779 1004 solver.cpp:245] Train net output #45: total_confidence = 1.60334e-07 | |
| I0407 15:16:43.939792 1004 sgd_solver.cpp:106] Iteration 1500, lr = 0.000997 | |
| I0407 15:17:21.963235 1004 solver.cpp:229] Iteration 2000, loss = 1.12813 | |
| I0407 15:17:21.963364 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 15:17:21.963383 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:17:21.963395 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:17:21.963408 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 15:17:21.963421 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 15:17:21.963433 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 15:17:21.963445 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 15:17:21.963457 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 15:17:21.963469 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:17:21.963482 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:17:21.963495 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:17:21.963505 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:17:21.963517 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:17:21.963528 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:17:21.963541 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:17:21.963551 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:17:21.963563 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:17:21.963577 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:17:21.963587 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:17:21.963599 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:17:21.963610 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:17:21.963623 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:17:21.963639 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.87842 (* 0.0454545 = 0.176292 loss) | |
| I0407 15:17:21.963652 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.52915 (* 0.0454545 = 0.160416 loss) | |
| I0407 15:17:21.963667 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.80902 (* 0.0454545 = 0.173137 loss) | |
| I0407 15:17:21.963681 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.60174 (* 0.0454545 = 0.163715 loss) | |
| I0407 15:17:21.963696 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.82678 (* 0.0454545 = 0.173944 loss) | |
| I0407 15:17:21.963709 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.02438 (* 0.0454545 = 0.137472 loss) | |
| I0407 15:17:21.963723 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.6835 (* 0.0454545 = 0.0765228 loss) | |
| I0407 15:17:21.963737 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.893967 (* 0.0454545 = 0.0406349 loss) | |
| I0407 15:17:21.963752 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.55225 (* 0.0454545 = 0.0251023 loss) | |
| I0407 15:17:21.963765 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0191349 (* 0.0454545 = 0.000869768 loss) | |
| I0407 15:17:21.963780 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000949246 (* 0.0454545 = 4.31476e-05 loss) | |
| I0407 15:17:21.963794 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000698698 (* 0.0454545 = 3.1759e-05 loss) | |
| I0407 15:17:21.963809 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000869426 (* 0.0454545 = 3.95194e-05 loss) | |
| I0407 15:17:21.963824 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00102098 (* 0.0454545 = 4.64084e-05 loss) | |
| I0407 15:17:21.963838 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000805288 (* 0.0454545 = 3.6604e-05 loss) | |
| I0407 15:17:21.963852 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000903746 (* 0.0454545 = 4.10794e-05 loss) | |
| I0407 15:17:21.963866 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.00093384 (* 0.0454545 = 4.24473e-05 loss) | |
| I0407 15:17:21.963898 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000993297 (* 0.0454545 = 4.51499e-05 loss) | |
| I0407 15:17:21.963914 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000889562 (* 0.0454545 = 4.04346e-05 loss) | |
| I0407 15:17:21.963932 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000926217 (* 0.0454545 = 4.21008e-05 loss) | |
| I0407 15:17:21.963948 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000912629 (* 0.0454545 = 4.14831e-05 loss) | |
| I0407 15:17:21.963961 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00095271 (* 0.0454545 = 4.3305e-05 loss) | |
| I0407 15:17:21.963974 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:17:21.963986 1004 solver.cpp:245] Train net output #45: total_confidence = 6.54347e-07 | |
| I0407 15:17:21.963999 1004 sgd_solver.cpp:106] Iteration 2000, lr = 0.000996 | |
| I0407 15:18:00.979277 1004 solver.cpp:229] Iteration 2500, loss = 1.11928 | |
| I0407 15:18:00.979374 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 15:18:00.979404 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:18:00.979428 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:18:00.979451 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 15:18:00.979473 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.4375 | |
| I0407 15:18:00.979495 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.6875 | |
| I0407 15:18:00.979516 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 15:18:00.979542 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.75 | |
| I0407 15:18:00.979565 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:18:00.979585 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:18:00.979606 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:18:00.979626 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:18:00.979647 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:18:00.979671 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:18:00.979691 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:18:00.979712 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:18:00.979732 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:18:00.979751 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:18:00.979771 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:18:00.979792 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:18:00.979812 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:18:00.979835 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:18:00.979861 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.57533 (* 0.0454545 = 0.162515 loss) | |
| I0407 15:18:00.979887 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.83735 (* 0.0454545 = 0.174425 loss) | |
| I0407 15:18:00.979912 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.74756 (* 0.0454545 = 0.170344 loss) | |
| I0407 15:18:00.979938 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.78415 (* 0.0454545 = 0.172007 loss) | |
| I0407 15:18:00.979964 1004 solver.cpp:245] Train net output #26: loss/loss05 = 2.86269 (* 0.0454545 = 0.130122 loss) | |
| I0407 15:18:00.979989 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.09067 (* 0.0454545 = 0.0950303 loss) | |
| I0407 15:18:00.980012 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.62928 (* 0.0454545 = 0.074058 loss) | |
| I0407 15:18:00.980039 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.58028 (* 0.0454545 = 0.0718307 loss) | |
| I0407 15:18:00.980067 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0490309 (* 0.0454545 = 0.00222868 loss) | |
| I0407 15:18:00.980098 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0197341 (* 0.0454545 = 0.000897006 loss) | |
| I0407 15:18:00.980123 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000980531 (* 0.0454545 = 4.45696e-05 loss) | |
| I0407 15:18:00.980147 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000756962 (* 0.0454545 = 3.44074e-05 loss) | |
| I0407 15:18:00.980172 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000823396 (* 0.0454545 = 3.74271e-05 loss) | |
| I0407 15:18:00.980197 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00100932 (* 0.0454545 = 4.58782e-05 loss) | |
| I0407 15:18:00.980222 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.00085444 (* 0.0454545 = 3.88382e-05 loss) | |
| I0407 15:18:00.980247 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000907814 (* 0.0454545 = 4.12643e-05 loss) | |
| I0407 15:18:00.980273 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000840721 (* 0.0454545 = 3.82146e-05 loss) | |
| I0407 15:18:00.980319 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.00100567 (* 0.0454545 = 4.57122e-05 loss) | |
| I0407 15:18:00.980347 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000989316 (* 0.0454545 = 4.49689e-05 loss) | |
| I0407 15:18:00.980373 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000875047 (* 0.0454545 = 3.97749e-05 loss) | |
| I0407 15:18:00.980398 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000967429 (* 0.0454545 = 4.39741e-05 loss) | |
| I0407 15:18:00.980422 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000937313 (* 0.0454545 = 4.26051e-05 loss) | |
| I0407 15:18:00.980444 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:18:00.980464 1004 solver.cpp:245] Train net output #45: total_confidence = 1.58938e-06 | |
| I0407 15:18:00.980485 1004 sgd_solver.cpp:106] Iteration 2500, lr = 0.000995 | |
| I0407 15:18:38.995471 1004 solver.cpp:229] Iteration 3000, loss = 1.11299 | |
| I0407 15:18:38.995611 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 15:18:38.995631 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:18:38.995645 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 15:18:38.995656 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 15:18:38.995668 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 15:18:38.995681 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 15:18:38.995692 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.625 | |
| I0407 15:18:38.995704 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 15:18:38.995717 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:18:38.995728 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:18:38.995739 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:18:38.995751 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:18:38.995762 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:18:38.995774 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:18:38.995785 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:18:38.995797 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:18:38.995808 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:18:38.995828 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:18:38.995851 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:18:38.995868 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:18:38.995880 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:18:38.995892 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:18:38.995908 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.8553 (* 0.0454545 = 0.175241 loss) | |
| I0407 15:18:38.995924 1004 solver.cpp:245] Train net output #23: loss/loss02 = 4.16645 (* 0.0454545 = 0.189384 loss) | |
| I0407 15:18:38.995939 1004 solver.cpp:245] Train net output #24: loss/loss03 = 4.21365 (* 0.0454545 = 0.191529 loss) | |
| I0407 15:18:38.995952 1004 solver.cpp:245] Train net output #25: loss/loss04 = 4.32652 (* 0.0454545 = 0.19666 loss) | |
| I0407 15:18:38.995966 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.91439 (* 0.0454545 = 0.177927 loss) | |
| I0407 15:18:38.995980 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.69368 (* 0.0454545 = 0.167895 loss) | |
| I0407 15:18:38.996000 1004 solver.cpp:245] Train net output #28: loss/loss07 = 2.28152 (* 0.0454545 = 0.103706 loss) | |
| I0407 15:18:38.996014 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.798591 (* 0.0454545 = 0.0362996 loss) | |
| I0407 15:18:38.996028 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0761353 (* 0.0454545 = 0.0034607 loss) | |
| I0407 15:18:38.996042 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0348608 (* 0.0454545 = 0.00158458 loss) | |
| I0407 15:18:38.996057 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.00220238 (* 0.0454545 = 0.000100108 loss) | |
| I0407 15:18:38.996070 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00201854 (* 0.0454545 = 9.17517e-05 loss) | |
| I0407 15:18:38.996085 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.00191198 (* 0.0454545 = 8.69081e-05 loss) | |
| I0407 15:18:38.996099 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00208781 (* 0.0454545 = 9.49003e-05 loss) | |
| I0407 15:18:38.996114 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.00214207 (* 0.0454545 = 9.7367e-05 loss) | |
| I0407 15:18:38.996129 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.00209638 (* 0.0454545 = 9.52899e-05 loss) | |
| I0407 15:18:38.996142 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.00213479 (* 0.0454545 = 9.70357e-05 loss) | |
| I0407 15:18:38.996183 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.00213411 (* 0.0454545 = 9.70051e-05 loss) | |
| I0407 15:18:38.996199 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00209823 (* 0.0454545 = 9.53743e-05 loss) | |
| I0407 15:18:38.996213 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.00211056 (* 0.0454545 = 9.59345e-05 loss) | |
| I0407 15:18:38.996227 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00222981 (* 0.0454545 = 0.000101355 loss) | |
| I0407 15:18:38.996242 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00221842 (* 0.0454545 = 0.000100837 loss) | |
| I0407 15:18:38.996253 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:18:38.996265 1004 solver.cpp:245] Train net output #45: total_confidence = 8.40228e-07 | |
| I0407 15:18:38.996279 1004 sgd_solver.cpp:106] Iteration 3000, lr = 0.000994 | |
| I0407 15:19:16.850486 1004 solver.cpp:229] Iteration 3500, loss = 1.10823 | |
| I0407 15:19:16.850600 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 15:19:16.850618 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:19:16.850631 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:19:16.850644 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 15:19:16.850656 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 15:19:16.850668 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 15:19:16.850680 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 15:19:16.850692 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 15:19:16.850704 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:19:16.850716 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 15:19:16.850728 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:19:16.850739 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:19:16.850751 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:19:16.850764 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:19:16.850775 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:19:16.850786 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:19:16.850797 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:19:16.850810 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:19:16.850821 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:19:16.850832 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:19:16.850843 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:19:16.850855 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:19:16.850870 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.54985 (* 0.0454545 = 0.161357 loss) | |
| I0407 15:19:16.850885 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.60507 (* 0.0454545 = 0.163867 loss) | |
| I0407 15:19:16.850899 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.59081 (* 0.0454545 = 0.163219 loss) | |
| I0407 15:19:16.850914 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.46809 (* 0.0454545 = 0.15764 loss) | |
| I0407 15:19:16.850930 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.07715 (* 0.0454545 = 0.13987 loss) | |
| I0407 15:19:16.850944 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.01354 (* 0.0454545 = 0.136979 loss) | |
| I0407 15:19:16.850957 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.16915 (* 0.0454545 = 0.053143 loss) | |
| I0407 15:19:16.850971 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.412662 (* 0.0454545 = 0.0187574 loss) | |
| I0407 15:19:16.850986 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.488963 (* 0.0454545 = 0.0222256 loss) | |
| I0407 15:19:16.851001 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.501588 (* 0.0454545 = 0.0227995 loss) | |
| I0407 15:19:16.851014 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000792313 (* 0.0454545 = 3.60142e-05 loss) | |
| I0407 15:19:16.851028 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000737096 (* 0.0454545 = 3.35044e-05 loss) | |
| I0407 15:19:16.851042 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000742769 (* 0.0454545 = 3.37622e-05 loss) | |
| I0407 15:19:16.851058 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000887919 (* 0.0454545 = 4.03599e-05 loss) | |
| I0407 15:19:16.851071 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000770642 (* 0.0454545 = 3.50292e-05 loss) | |
| I0407 15:19:16.851084 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000742899 (* 0.0454545 = 3.37682e-05 loss) | |
| I0407 15:19:16.851099 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.00084231 (* 0.0454545 = 3.82868e-05 loss) | |
| I0407 15:19:16.851130 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000767102 (* 0.0454545 = 3.48683e-05 loss) | |
| I0407 15:19:16.851145 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000805799 (* 0.0454545 = 3.66272e-05 loss) | |
| I0407 15:19:16.851158 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000820679 (* 0.0454545 = 3.73036e-05 loss) | |
| I0407 15:19:16.851173 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000898887 (* 0.0454545 = 4.08585e-05 loss) | |
| I0407 15:19:16.851186 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000797604 (* 0.0454545 = 3.62547e-05 loss) | |
| I0407 15:19:16.851198 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:19:16.851210 1004 solver.cpp:245] Train net output #45: total_confidence = 4.00025e-06 | |
| I0407 15:19:16.851223 1004 sgd_solver.cpp:106] Iteration 3500, lr = 0.000993 | |
| I0407 15:19:54.736944 1004 solver.cpp:229] Iteration 4000, loss = 1.10626 | |
| I0407 15:19:54.737049 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 15:19:54.737081 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:19:54.737104 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:19:54.737128 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 15:19:54.737149 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 15:19:54.737171 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5 | |
| I0407 15:19:54.737195 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.9375 | |
| I0407 15:19:54.737217 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 15:19:54.737237 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:19:54.737258 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:19:54.737280 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:19:54.737303 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:19:54.737323 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:19:54.737344 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:19:54.737363 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:19:54.737385 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:19:54.737407 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:19:54.737428 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:19:54.737448 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:19:54.737468 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:19:54.737488 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:19:54.737509 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:19:54.737535 1004 solver.cpp:245] Train net output #22: loss/loss01 = 4.21605 (* 0.0454545 = 0.191639 loss) | |
| I0407 15:19:54.737563 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.84862 (* 0.0454545 = 0.174937 loss) | |
| I0407 15:19:54.737589 1004 solver.cpp:245] Train net output #24: loss/loss03 = 4.34773 (* 0.0454545 = 0.197624 loss) | |
| I0407 15:19:54.737612 1004 solver.cpp:245] Train net output #25: loss/loss04 = 4.38637 (* 0.0454545 = 0.199381 loss) | |
| I0407 15:19:54.737634 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.92735 (* 0.0454545 = 0.178516 loss) | |
| I0407 15:19:54.737659 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.57393 (* 0.0454545 = 0.116997 loss) | |
| I0407 15:19:54.737684 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.546458 (* 0.0454545 = 0.024839 loss) | |
| I0407 15:19:54.737709 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.0711791 (* 0.0454545 = 0.00323541 loss) | |
| I0407 15:19:54.737735 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0302873 (* 0.0454545 = 0.00137669 loss) | |
| I0407 15:19:54.737761 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0108092 (* 0.0454545 = 0.000491328 loss) | |
| I0407 15:19:54.737788 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000363705 (* 0.0454545 = 1.65321e-05 loss) | |
| I0407 15:19:54.737814 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000333516 (* 0.0454545 = 1.51598e-05 loss) | |
| I0407 15:19:54.737839 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000357958 (* 0.0454545 = 1.62708e-05 loss) | |
| I0407 15:19:54.737864 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000348727 (* 0.0454545 = 1.58512e-05 loss) | |
| I0407 15:19:54.737890 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000324335 (* 0.0454545 = 1.47425e-05 loss) | |
| I0407 15:19:54.737915 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000353868 (* 0.0454545 = 1.60849e-05 loss) | |
| I0407 15:19:54.737939 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000363924 (* 0.0454545 = 1.6542e-05 loss) | |
| I0407 15:19:54.737987 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000352524 (* 0.0454545 = 1.60238e-05 loss) | |
| I0407 15:19:54.738013 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000356849 (* 0.0454545 = 1.62204e-05 loss) | |
| I0407 15:19:54.738039 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000340102 (* 0.0454545 = 1.54592e-05 loss) | |
| I0407 15:19:54.738064 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000355522 (* 0.0454545 = 1.61601e-05 loss) | |
| I0407 15:19:54.738092 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000335019 (* 0.0454545 = 1.52281e-05 loss) | |
| I0407 15:19:54.738114 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:19:54.738139 1004 solver.cpp:245] Train net output #45: total_confidence = 8.82845e-06 | |
| I0407 15:19:54.738163 1004 sgd_solver.cpp:106] Iteration 4000, lr = 0.000992 | |
| I0407 15:20:33.216863 1004 solver.cpp:229] Iteration 4500, loss = 1.10251 | |
| I0407 15:20:33.216960 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 15:20:33.216989 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:20:33.217012 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 15:20:33.217041 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 15:20:33.217062 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 15:20:33.217083 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.25 | |
| I0407 15:20:33.217105 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 15:20:33.217128 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 15:20:33.217149 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:20:33.217170 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:20:33.217190 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:20:33.217209 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:20:33.217231 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:20:33.217253 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:20:33.217274 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:20:33.217294 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:20:33.217315 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:20:33.217335 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:20:33.217355 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:20:33.217376 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:20:33.217396 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:20:33.217418 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:20:33.217445 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.55257 (* 0.0454545 = 0.161481 loss) | |
| I0407 15:20:33.217473 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.83471 (* 0.0454545 = 0.174305 loss) | |
| I0407 15:20:33.217497 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.90317 (* 0.0454545 = 0.177417 loss) | |
| I0407 15:20:33.217524 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.82169 (* 0.0454545 = 0.173713 loss) | |
| I0407 15:20:33.217548 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.48073 (* 0.0454545 = 0.158215 loss) | |
| I0407 15:20:33.217573 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.49817 (* 0.0454545 = 0.159008 loss) | |
| I0407 15:20:33.217598 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.59218 (* 0.0454545 = 0.0723718 loss) | |
| I0407 15:20:33.217623 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.426254 (* 0.0454545 = 0.0193752 loss) | |
| I0407 15:20:33.217651 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0632686 (* 0.0454545 = 0.00287585 loss) | |
| I0407 15:20:33.217677 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0239243 (* 0.0454545 = 0.00108747 loss) | |
| I0407 15:20:33.217702 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.00100283 (* 0.0454545 = 4.55831e-05 loss) | |
| I0407 15:20:33.217727 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000989121 (* 0.0454545 = 4.496e-05 loss) | |
| I0407 15:20:33.217753 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.00105885 (* 0.0454545 = 4.81298e-05 loss) | |
| I0407 15:20:33.217778 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000949242 (* 0.0454545 = 4.31474e-05 loss) | |
| I0407 15:20:33.217803 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000990591 (* 0.0454545 = 4.50269e-05 loss) | |
| I0407 15:20:33.217828 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.00102011 (* 0.0454545 = 4.63687e-05 loss) | |
| I0407 15:20:33.217854 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.00109568 (* 0.0454545 = 4.98037e-05 loss) | |
| I0407 15:20:33.217898 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.00101078 (* 0.0454545 = 4.59445e-05 loss) | |
| I0407 15:20:33.217926 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000967165 (* 0.0454545 = 4.3962e-05 loss) | |
| I0407 15:20:33.217953 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.00101809 (* 0.0454545 = 4.62767e-05 loss) | |
| I0407 15:20:33.217979 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00107889 (* 0.0454545 = 4.90407e-05 loss) | |
| I0407 15:20:33.218004 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00110452 (* 0.0454545 = 5.02055e-05 loss) | |
| I0407 15:20:33.218026 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:20:33.218045 1004 solver.cpp:245] Train net output #45: total_confidence = 7.22191e-07 | |
| I0407 15:20:33.218067 1004 sgd_solver.cpp:106] Iteration 4500, lr = 0.000991 | |
| I0407 15:21:11.562465 1004 solver.cpp:338] Iteration 5000, Testing net (#0) | |
| I0407 15:21:19.511219 1004 solver.cpp:393] Test loss: 0.999263 | |
| I0407 15:21:19.511276 1004 solver.cpp:406] Test net output #0: loss/accuracy01 = 0 | |
| I0407 15:21:19.511293 1004 solver.cpp:406] Test net output #1: loss/accuracy02 = 0.124 | |
| I0407 15:21:19.511307 1004 solver.cpp:406] Test net output #2: loss/accuracy03 = 0.005 | |
| I0407 15:21:19.511337 1004 solver.cpp:406] Test net output #3: loss/accuracy04 = 0.09 | |
| I0407 15:21:19.511351 1004 solver.cpp:406] Test net output #4: loss/accuracy05 = 0.212 | |
| I0407 15:21:19.511373 1004 solver.cpp:406] Test net output #5: loss/accuracy06 = 0.501 | |
| I0407 15:21:19.511384 1004 solver.cpp:406] Test net output #6: loss/accuracy07 = 0.894 | |
| I0407 15:21:19.511396 1004 solver.cpp:406] Test net output #7: loss/accuracy08 = 0.97 | |
| I0407 15:21:19.511409 1004 solver.cpp:406] Test net output #8: loss/accuracy09 = 0.995 | |
| I0407 15:21:19.511420 1004 solver.cpp:406] Test net output #9: loss/accuracy10 = 0.998 | |
| I0407 15:21:19.511437 1004 solver.cpp:406] Test net output #10: loss/accuracy11 = 1 | |
| I0407 15:21:19.511450 1004 solver.cpp:406] Test net output #11: loss/accuracy12 = 1 | |
| I0407 15:21:19.511461 1004 solver.cpp:406] Test net output #12: loss/accuracy13 = 1 | |
| I0407 15:21:19.511472 1004 solver.cpp:406] Test net output #13: loss/accuracy14 = 1 | |
| I0407 15:21:19.511483 1004 solver.cpp:406] Test net output #14: loss/accuracy15 = 1 | |
| I0407 15:21:19.511494 1004 solver.cpp:406] Test net output #15: loss/accuracy16 = 1 | |
| I0407 15:21:19.511505 1004 solver.cpp:406] Test net output #16: loss/accuracy17 = 1 | |
| I0407 15:21:19.511518 1004 solver.cpp:406] Test net output #17: loss/accuracy18 = 1 | |
| I0407 15:21:19.511534 1004 solver.cpp:406] Test net output #18: loss/accuracy19 = 1 | |
| I0407 15:21:19.511546 1004 solver.cpp:406] Test net output #19: loss/accuracy20 = 1 | |
| I0407 15:21:19.511557 1004 solver.cpp:406] Test net output #20: loss/accuracy21 = 1 | |
| I0407 15:21:19.511569 1004 solver.cpp:406] Test net output #21: loss/accuracy22 = 1 | |
| I0407 15:21:19.511584 1004 solver.cpp:406] Test net output #22: loss/loss01 = 3.53264 (* 0.0454545 = 0.160575 loss) | |
| I0407 15:21:19.511597 1004 solver.cpp:406] Test net output #23: loss/loss02 = 3.53075 (* 0.0454545 = 0.160489 loss) | |
| I0407 15:21:19.511615 1004 solver.cpp:406] Test net output #24: loss/loss03 = 3.61352 (* 0.0454545 = 0.164251 loss) | |
| I0407 15:21:19.511627 1004 solver.cpp:406] Test net output #25: loss/loss04 = 3.71816 (* 0.0454545 = 0.169007 loss) | |
| I0407 15:21:19.511641 1004 solver.cpp:406] Test net output #26: loss/loss05 = 3.56834 (* 0.0454545 = 0.162197 loss) | |
| I0407 15:21:19.511654 1004 solver.cpp:406] Test net output #27: loss/loss06 = 2.54753 (* 0.0454545 = 0.115797 loss) | |
| I0407 15:21:19.511668 1004 solver.cpp:406] Test net output #28: loss/loss07 = 0.925933 (* 0.0454545 = 0.0420879 loss) | |
| I0407 15:21:19.511682 1004 solver.cpp:406] Test net output #29: loss/loss08 = 0.363966 (* 0.0454545 = 0.0165439 loss) | |
| I0407 15:21:19.511696 1004 solver.cpp:406] Test net output #30: loss/loss09 = 0.100998 (* 0.0454545 = 0.00459081 loss) | |
| I0407 15:21:19.511709 1004 solver.cpp:406] Test net output #31: loss/loss10 = 0.0472559 (* 0.0454545 = 0.002148 loss) | |
| I0407 15:21:19.511723 1004 solver.cpp:406] Test net output #32: loss/loss11 = 0.00290662 (* 0.0454545 = 0.000132119 loss) | |
| I0407 15:21:19.511737 1004 solver.cpp:406] Test net output #33: loss/loss12 = 0.00281991 (* 0.0454545 = 0.000128178 loss) | |
| I0407 15:21:19.511751 1004 solver.cpp:406] Test net output #34: loss/loss13 = 0.00284474 (* 0.0454545 = 0.000129306 loss) | |
| I0407 15:21:19.511775 1004 solver.cpp:406] Test net output #35: loss/loss14 = 0.0029047 (* 0.0454545 = 0.000132032 loss) | |
| I0407 15:21:19.511788 1004 solver.cpp:406] Test net output #36: loss/loss15 = 0.00289503 (* 0.0454545 = 0.000131592 loss) | |
| I0407 15:21:19.511802 1004 solver.cpp:406] Test net output #37: loss/loss16 = 0.00290745 (* 0.0454545 = 0.000132157 loss) | |
| I0407 15:21:19.511817 1004 solver.cpp:406] Test net output #38: loss/loss17 = 0.00289841 (* 0.0454545 = 0.000131746 loss) | |
| I0407 15:21:19.511870 1004 solver.cpp:406] Test net output #39: loss/loss18 = 0.00289845 (* 0.0454545 = 0.000131748 loss) | |
| I0407 15:21:19.511885 1004 solver.cpp:406] Test net output #40: loss/loss19 = 0.00291969 (* 0.0454545 = 0.000132713 loss) | |
| I0407 15:21:19.511899 1004 solver.cpp:406] Test net output #41: loss/loss20 = 0.00291029 (* 0.0454545 = 0.000132286 loss) | |
| I0407 15:21:19.511914 1004 solver.cpp:406] Test net output #42: loss/loss21 = 0.00291475 (* 0.0454545 = 0.000132489 loss) | |
| I0407 15:21:19.511930 1004 solver.cpp:406] Test net output #43: loss/loss22 = 0.00288478 (* 0.0454545 = 0.000131127 loss) | |
| I0407 15:21:19.511942 1004 solver.cpp:406] Test net output #44: total_accuracy = 0 | |
| I0407 15:21:19.511955 1004 solver.cpp:406] Test net output #45: total_confidence = 1.05245e-06 | |
| I0407 15:21:19.534677 1004 solver.cpp:229] Iteration 5000, loss = 1.10004 | |
| I0407 15:21:19.534714 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 15:21:19.534730 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:21:19.534744 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:21:19.534755 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 15:21:19.534767 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 15:21:19.534780 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 15:21:19.534792 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 15:21:19.534813 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 15:21:19.534826 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:21:19.534837 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:21:19.534849 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:21:19.534862 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:21:19.534873 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:21:19.534884 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:21:19.534896 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:21:19.534907 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:21:19.534919 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:21:19.534930 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:21:19.534942 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:21:19.534953 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:21:19.534965 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:21:19.534976 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:21:19.534991 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.91312 (* 0.0454545 = 0.177869 loss) | |
| I0407 15:21:19.535006 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.83994 (* 0.0454545 = 0.174543 loss) | |
| I0407 15:21:19.535019 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.90418 (* 0.0454545 = 0.177463 loss) | |
| I0407 15:21:19.535032 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.80887 (* 0.0454545 = 0.17313 loss) | |
| I0407 15:21:19.535046 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.69504 (* 0.0454545 = 0.167956 loss) | |
| I0407 15:21:19.535060 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.93824 (* 0.0454545 = 0.133556 loss) | |
| I0407 15:21:19.535078 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.59527 (* 0.0454545 = 0.0725123 loss) | |
| I0407 15:21:19.535091 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.502549 (* 0.0454545 = 0.0228431 loss) | |
| I0407 15:21:19.535105 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0510603 (* 0.0454545 = 0.00232093 loss) | |
| I0407 15:21:19.535120 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0213895 (* 0.0454545 = 0.000972248 loss) | |
| I0407 15:21:19.535151 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.00114966 (* 0.0454545 = 5.22571e-05 loss) | |
| I0407 15:21:19.535166 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00109962 (* 0.0454545 = 4.99829e-05 loss) | |
| I0407 15:21:19.535181 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.00110016 (* 0.0454545 = 5.00072e-05 loss) | |
| I0407 15:21:19.535194 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00116717 (* 0.0454545 = 5.30532e-05 loss) | |
| I0407 15:21:19.535209 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.00126296 (* 0.0454545 = 5.74075e-05 loss) | |
| I0407 15:21:19.535223 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.00118681 (* 0.0454545 = 5.39458e-05 loss) | |
| I0407 15:21:19.535238 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.00127512 (* 0.0454545 = 5.79601e-05 loss) | |
| I0407 15:21:19.535253 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.00125269 (* 0.0454545 = 5.69405e-05 loss) | |
| I0407 15:21:19.535266 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00113689 (* 0.0454545 = 5.16767e-05 loss) | |
| I0407 15:21:19.535280 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.00116413 (* 0.0454545 = 5.29148e-05 loss) | |
| I0407 15:21:19.535295 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00124413 (* 0.0454545 = 5.65512e-05 loss) | |
| I0407 15:21:19.535308 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00117186 (* 0.0454545 = 5.32665e-05 loss) | |
| I0407 15:21:19.535338 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:21:19.535352 1004 solver.cpp:245] Train net output #45: total_confidence = 8.79514e-07 | |
| I0407 15:21:19.535367 1004 sgd_solver.cpp:106] Iteration 5000, lr = 0.00099 | |
| I0407 15:21:57.637063 1004 solver.cpp:229] Iteration 5500, loss = 1.09717 | |
| I0407 15:21:57.637166 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:21:57.637184 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:21:57.637197 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 15:21:57.637210 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 15:21:57.637223 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.0625 | |
| I0407 15:21:57.637234 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.25 | |
| I0407 15:21:57.637246 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.5 | |
| I0407 15:21:57.637259 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 15:21:57.637270 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:21:57.637282 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:21:57.637295 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:21:57.637306 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:21:57.637317 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:21:57.637329 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:21:57.637341 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:21:57.637352 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:21:57.637363 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:21:57.637375 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:21:57.637387 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:21:57.637398 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:21:57.637409 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:21:57.637421 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:21:57.637436 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.79173 (* 0.0454545 = 0.172352 loss) | |
| I0407 15:21:57.637451 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.61408 (* 0.0454545 = 0.164277 loss) | |
| I0407 15:21:57.637465 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.84771 (* 0.0454545 = 0.174896 loss) | |
| I0407 15:21:57.637478 1004 solver.cpp:245] Train net output #25: loss/loss04 = 4.01291 (* 0.0454545 = 0.182405 loss) | |
| I0407 15:21:57.637492 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.90572 (* 0.0454545 = 0.177533 loss) | |
| I0407 15:21:57.637506 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.37495 (* 0.0454545 = 0.153407 loss) | |
| I0407 15:21:57.637519 1004 solver.cpp:245] Train net output #28: loss/loss07 = 2.73842 (* 0.0454545 = 0.124474 loss) | |
| I0407 15:21:57.637533 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.14427 (* 0.0454545 = 0.0520123 loss) | |
| I0407 15:21:57.637547 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.439913 (* 0.0454545 = 0.019996 loss) | |
| I0407 15:21:57.637562 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0158382 (* 0.0454545 = 0.000719917 loss) | |
| I0407 15:21:57.637575 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000708379 (* 0.0454545 = 3.21991e-05 loss) | |
| I0407 15:21:57.637589 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00065686 (* 0.0454545 = 2.98573e-05 loss) | |
| I0407 15:21:57.637603 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000656456 (* 0.0454545 = 2.98389e-05 loss) | |
| I0407 15:21:57.637617 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000701138 (* 0.0454545 = 3.18699e-05 loss) | |
| I0407 15:21:57.637632 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000698081 (* 0.0454545 = 3.1731e-05 loss) | |
| I0407 15:21:57.637646 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000764427 (* 0.0454545 = 3.47467e-05 loss) | |
| I0407 15:21:57.637660 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000691944 (* 0.0454545 = 3.1452e-05 loss) | |
| I0407 15:21:57.637691 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000723272 (* 0.0454545 = 3.2876e-05 loss) | |
| I0407 15:21:57.637706 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000766797 (* 0.0454545 = 3.48544e-05 loss) | |
| I0407 15:21:57.637720 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000659204 (* 0.0454545 = 2.99638e-05 loss) | |
| I0407 15:21:57.637734 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00065288 (* 0.0454545 = 2.96764e-05 loss) | |
| I0407 15:21:57.637748 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000752718 (* 0.0454545 = 3.42145e-05 loss) | |
| I0407 15:21:57.637760 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:21:57.637773 1004 solver.cpp:245] Train net output #45: total_confidence = 3.14734e-06 | |
| I0407 15:21:57.637785 1004 sgd_solver.cpp:106] Iteration 5500, lr = 0.000989 | |
| I0407 15:22:35.506170 1004 solver.cpp:229] Iteration 6000, loss = 1.09658 | |
| I0407 15:22:35.506290 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 15:22:35.506319 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:22:35.506341 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:22:35.506362 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 15:22:35.506386 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.3125 | |
| I0407 15:22:35.506407 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5 | |
| I0407 15:22:35.506428 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 15:22:35.506448 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 15:22:35.506467 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.875 | |
| I0407 15:22:35.506489 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:22:35.506511 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:22:35.506531 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:22:35.506552 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:22:35.506572 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:22:35.506592 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:22:35.506613 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:22:35.506633 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:22:35.506654 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:22:35.506675 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:22:35.506697 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:22:35.506718 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:22:35.506738 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:22:35.506765 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.80443 (* 0.0454545 = 0.172929 loss) | |
| I0407 15:22:35.506793 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.79986 (* 0.0454545 = 0.172721 loss) | |
| I0407 15:22:35.506816 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.69053 (* 0.0454545 = 0.167751 loss) | |
| I0407 15:22:35.506841 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.6618 (* 0.0454545 = 0.166446 loss) | |
| I0407 15:22:35.506866 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.03277 (* 0.0454545 = 0.137853 loss) | |
| I0407 15:22:35.506891 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.50725 (* 0.0454545 = 0.113966 loss) | |
| I0407 15:22:35.506916 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.92509 (* 0.0454545 = 0.0875039 loss) | |
| I0407 15:22:35.506943 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.920271 (* 0.0454545 = 0.0418305 loss) | |
| I0407 15:22:35.506970 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.970482 (* 0.0454545 = 0.0441128 loss) | |
| I0407 15:22:35.506995 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0133275 (* 0.0454545 = 0.000605796 loss) | |
| I0407 15:22:35.507021 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000332778 (* 0.0454545 = 1.51263e-05 loss) | |
| I0407 15:22:35.507046 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000321548 (* 0.0454545 = 1.46158e-05 loss) | |
| I0407 15:22:35.507071 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.00030724 (* 0.0454545 = 1.39655e-05 loss) | |
| I0407 15:22:35.507102 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00031203 (* 0.0454545 = 1.41832e-05 loss) | |
| I0407 15:22:35.507127 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000319697 (* 0.0454545 = 1.45317e-05 loss) | |
| I0407 15:22:35.507151 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000318548 (* 0.0454545 = 1.44795e-05 loss) | |
| I0407 15:22:35.507176 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000326527 (* 0.0454545 = 1.48421e-05 loss) | |
| I0407 15:22:35.508288 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000317491 (* 0.0454545 = 1.44314e-05 loss) | |
| I0407 15:22:35.508306 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000340474 (* 0.0454545 = 1.54761e-05 loss) | |
| I0407 15:22:35.508316 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000325611 (* 0.0454545 = 1.48005e-05 loss) | |
| I0407 15:22:35.508325 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00030224 (* 0.0454545 = 1.37382e-05 loss) | |
| I0407 15:22:35.508334 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000348682 (* 0.0454545 = 1.58492e-05 loss) | |
| I0407 15:22:35.508342 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:22:35.508349 1004 solver.cpp:245] Train net output #45: total_confidence = 2.27222e-05 | |
| I0407 15:22:35.508358 1004 sgd_solver.cpp:106] Iteration 6000, lr = 0.000988 | |
| I0407 15:23:13.233979 1004 solver.cpp:229] Iteration 6500, loss = 1.09872 | |
| I0407 15:23:13.234107 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:23:13.234127 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:23:13.234140 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:23:13.234154 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 15:23:13.234166 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 15:23:13.234177 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.25 | |
| I0407 15:23:13.234189 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 15:23:13.234202 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 15:23:13.234215 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:23:13.234226 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:23:13.234237 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:23:13.234249 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:23:13.234261 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:23:13.234273 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:23:13.234285 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:23:13.234297 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:23:13.234308 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:23:13.234320 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:23:13.234331 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:23:13.234344 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:23:13.234355 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:23:13.234366 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:23:13.234382 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.66821 (* 0.0454545 = 0.166737 loss) | |
| I0407 15:23:13.234396 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.62617 (* 0.0454545 = 0.164826 loss) | |
| I0407 15:23:13.234411 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.69367 (* 0.0454545 = 0.167894 loss) | |
| I0407 15:23:13.234424 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.72673 (* 0.0454545 = 0.169397 loss) | |
| I0407 15:23:13.234437 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.38237 (* 0.0454545 = 0.153744 loss) | |
| I0407 15:23:13.234452 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.11975 (* 0.0454545 = 0.141807 loss) | |
| I0407 15:23:13.234464 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.32785 (* 0.0454545 = 0.0603566 loss) | |
| I0407 15:23:13.234478 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.775833 (* 0.0454545 = 0.0352651 loss) | |
| I0407 15:23:13.234493 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.504426 (* 0.0454545 = 0.0229284 loss) | |
| I0407 15:23:13.234506 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.013668 (* 0.0454545 = 0.000621272 loss) | |
| I0407 15:23:13.234521 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000294894 (* 0.0454545 = 1.34043e-05 loss) | |
| I0407 15:23:13.234535 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000303715 (* 0.0454545 = 1.38052e-05 loss) | |
| I0407 15:23:13.234549 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000290809 (* 0.0454545 = 1.32186e-05 loss) | |
| I0407 15:23:13.234563 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000308025 (* 0.0454545 = 1.40011e-05 loss) | |
| I0407 15:23:13.234577 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000320732 (* 0.0454545 = 1.45787e-05 loss) | |
| I0407 15:23:13.234591 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000331979 (* 0.0454545 = 1.509e-05 loss) | |
| I0407 15:23:13.234606 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000286088 (* 0.0454545 = 1.3004e-05 loss) | |
| I0407 15:23:13.234632 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000319642 (* 0.0454545 = 1.45292e-05 loss) | |
| I0407 15:23:13.234648 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000316111 (* 0.0454545 = 1.43687e-05 loss) | |
| I0407 15:23:13.234661 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000307771 (* 0.0454545 = 1.39896e-05 loss) | |
| I0407 15:23:13.234675 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000313918 (* 0.0454545 = 1.4269e-05 loss) | |
| I0407 15:23:13.234689 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000330905 (* 0.0454545 = 1.50411e-05 loss) | |
| I0407 15:23:13.234701 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:23:13.234726 1004 solver.cpp:245] Train net output #45: total_confidence = 6.00117e-06 | |
| I0407 15:23:13.234740 1004 sgd_solver.cpp:106] Iteration 6500, lr = 0.000987 | |
| I0407 15:23:51.690795 1004 solver.cpp:229] Iteration 7000, loss = 1.09281 | |
| I0407 15:23:51.690913 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:23:51.690943 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:23:51.690966 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:23:51.690989 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 15:23:51.691011 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 15:23:51.691032 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 15:23:51.691054 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.9375 | |
| I0407 15:23:51.691076 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 15:23:51.691098 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:23:51.691119 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:23:51.691138 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:23:51.691159 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:23:51.691179 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:23:51.691201 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:23:51.691222 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:23:51.691243 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:23:51.691264 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:23:51.691284 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:23:51.691305 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:23:51.691346 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:23:51.691371 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:23:51.691395 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:23:51.691423 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.64193 (* 0.0454545 = 0.165542 loss) | |
| I0407 15:23:51.691449 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.60828 (* 0.0454545 = 0.164013 loss) | |
| I0407 15:23:51.691474 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.5754 (* 0.0454545 = 0.162518 loss) | |
| I0407 15:23:51.691499 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.66556 (* 0.0454545 = 0.166616 loss) | |
| I0407 15:23:51.691524 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.27376 (* 0.0454545 = 0.148807 loss) | |
| I0407 15:23:51.691548 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.88166 (* 0.0454545 = 0.130984 loss) | |
| I0407 15:23:51.691572 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.665906 (* 0.0454545 = 0.0302685 loss) | |
| I0407 15:23:51.691599 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.483009 (* 0.0454545 = 0.021955 loss) | |
| I0407 15:23:51.691627 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0469936 (* 0.0454545 = 0.00213607 loss) | |
| I0407 15:23:51.691653 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0192439 (* 0.0454545 = 0.000874722 loss) | |
| I0407 15:23:51.691679 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000698892 (* 0.0454545 = 3.17678e-05 loss) | |
| I0407 15:23:51.691704 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000650005 (* 0.0454545 = 2.95457e-05 loss) | |
| I0407 15:23:51.691728 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000660747 (* 0.0454545 = 3.0034e-05 loss) | |
| I0407 15:23:51.691753 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000657241 (* 0.0454545 = 2.98746e-05 loss) | |
| I0407 15:23:51.691778 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000651664 (* 0.0454545 = 2.96211e-05 loss) | |
| I0407 15:23:51.691809 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000657918 (* 0.0454545 = 2.99053e-05 loss) | |
| I0407 15:23:51.691834 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000665974 (* 0.0454545 = 3.02715e-05 loss) | |
| I0407 15:23:51.691881 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000650807 (* 0.0454545 = 2.95822e-05 loss) | |
| I0407 15:23:51.691910 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00070984 (* 0.0454545 = 3.22655e-05 loss) | |
| I0407 15:23:51.691946 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000640587 (* 0.0454545 = 2.91176e-05 loss) | |
| I0407 15:23:51.691972 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000629206 (* 0.0454545 = 2.86003e-05 loss) | |
| I0407 15:23:51.691995 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000630954 (* 0.0454545 = 2.86797e-05 loss) | |
| I0407 15:23:51.692016 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:23:51.692035 1004 solver.cpp:245] Train net output #45: total_confidence = 1.61415e-05 | |
| I0407 15:23:51.692057 1004 sgd_solver.cpp:106] Iteration 7000, lr = 0.000986 | |
| I0407 15:24:30.120473 1004 solver.cpp:229] Iteration 7500, loss = 1.1012 | |
| I0407 15:24:30.120589 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:24:30.120620 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:24:30.120641 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 15:24:30.120664 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 15:24:30.120687 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.3125 | |
| I0407 15:24:30.120707 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 15:24:30.120728 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 15:24:30.120748 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 15:24:30.120770 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:24:30.120792 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:24:30.120813 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:24:30.120834 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:24:30.120854 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:24:30.120874 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:24:30.120895 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:24:30.120915 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:24:30.120942 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:24:30.120965 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:24:30.120985 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:24:30.121006 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:24:30.121026 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:24:30.121047 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:24:30.121073 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.36744 (* 0.0454545 = 0.153066 loss) | |
| I0407 15:24:30.121098 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.4978 (* 0.0454545 = 0.158991 loss) | |
| I0407 15:24:30.121124 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.4528 (* 0.0454545 = 0.156946 loss) | |
| I0407 15:24:30.121150 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.5017 (* 0.0454545 = 0.159168 loss) | |
| I0407 15:24:30.121176 1004 solver.cpp:245] Train net output #26: loss/loss05 = 2.94386 (* 0.0454545 = 0.133812 loss) | |
| I0407 15:24:30.121201 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.9983 (* 0.0454545 = 0.136287 loss) | |
| I0407 15:24:30.121227 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.66838 (* 0.0454545 = 0.0758354 loss) | |
| I0407 15:24:30.121251 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.781154 (* 0.0454545 = 0.035507 loss) | |
| I0407 15:24:30.121278 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.032961 (* 0.0454545 = 0.00149823 loss) | |
| I0407 15:24:30.121302 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0106804 (* 0.0454545 = 0.000485472 loss) | |
| I0407 15:24:30.121328 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000262091 (* 0.0454545 = 1.19132e-05 loss) | |
| I0407 15:24:30.121352 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000247212 (* 0.0454545 = 1.12369e-05 loss) | |
| I0407 15:24:30.121377 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.00026681 (* 0.0454545 = 1.21277e-05 loss) | |
| I0407 15:24:30.121403 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000256094 (* 0.0454545 = 1.16407e-05 loss) | |
| I0407 15:24:30.121430 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000241961 (* 0.0454545 = 1.09982e-05 loss) | |
| I0407 15:24:30.121455 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000259965 (* 0.0454545 = 1.18166e-05 loss) | |
| I0407 15:24:30.121480 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000247161 (* 0.0454545 = 1.12346e-05 loss) | |
| I0407 15:24:30.121526 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000263369 (* 0.0454545 = 1.19713e-05 loss) | |
| I0407 15:24:30.121551 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000255895 (* 0.0454545 = 1.16316e-05 loss) | |
| I0407 15:24:30.121577 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000265885 (* 0.0454545 = 1.20857e-05 loss) | |
| I0407 15:24:30.121604 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000232796 (* 0.0454545 = 1.05816e-05 loss) | |
| I0407 15:24:30.121631 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000239497 (* 0.0454545 = 1.08862e-05 loss) | |
| I0407 15:24:30.121654 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:24:30.121673 1004 solver.cpp:245] Train net output #45: total_confidence = 4.30421e-06 | |
| I0407 15:24:30.121695 1004 sgd_solver.cpp:106] Iteration 7500, lr = 0.000985 | |
| I0407 15:25:09.558084 1004 solver.cpp:229] Iteration 8000, loss = 1.09551 | |
| I0407 15:25:09.558225 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:25:09.558255 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:25:09.558277 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:25:09.558300 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 15:25:09.558323 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.3125 | |
| I0407 15:25:09.558344 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5 | |
| I0407 15:25:09.558367 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.875 | |
| I0407 15:25:09.558388 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 15:25:09.558409 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:25:09.558429 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:25:09.558449 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:25:09.558470 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:25:09.558491 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:25:09.558513 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:25:09.558534 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:25:09.558554 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:25:09.558574 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:25:09.558595 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:25:09.558614 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:25:09.558635 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:25:09.558655 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:25:09.558678 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:25:09.558706 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.73802 (* 0.0454545 = 0.16991 loss) | |
| I0407 15:25:09.558732 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.8136 (* 0.0454545 = 0.173345 loss) | |
| I0407 15:25:09.558758 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.60659 (* 0.0454545 = 0.163936 loss) | |
| I0407 15:25:09.558782 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.85492 (* 0.0454545 = 0.175223 loss) | |
| I0407 15:25:09.558807 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.08716 (* 0.0454545 = 0.140325 loss) | |
| I0407 15:25:09.558831 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.54703 (* 0.0454545 = 0.115774 loss) | |
| I0407 15:25:09.558856 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.831117 (* 0.0454545 = 0.0377781 loss) | |
| I0407 15:25:09.558882 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.101115 (* 0.0454545 = 0.00459611 loss) | |
| I0407 15:25:09.558909 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0339258 (* 0.0454545 = 0.00154208 loss) | |
| I0407 15:25:09.558936 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0126889 (* 0.0454545 = 0.000576767 loss) | |
| I0407 15:25:09.558962 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000382364 (* 0.0454545 = 1.73802e-05 loss) | |
| I0407 15:25:09.558987 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000366253 (* 0.0454545 = 1.66479e-05 loss) | |
| I0407 15:25:09.559011 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000332705 (* 0.0454545 = 1.5123e-05 loss) | |
| I0407 15:25:09.559036 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000369179 (* 0.0454545 = 1.67809e-05 loss) | |
| I0407 15:25:09.559062 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000349773 (* 0.0454545 = 1.58988e-05 loss) | |
| I0407 15:25:09.559090 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000367032 (* 0.0454545 = 1.66833e-05 loss) | |
| I0407 15:25:09.559116 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000373851 (* 0.0454545 = 1.69932e-05 loss) | |
| I0407 15:25:09.559165 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000363015 (* 0.0454545 = 1.65007e-05 loss) | |
| I0407 15:25:09.559192 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000365704 (* 0.0454545 = 1.66229e-05 loss) | |
| I0407 15:25:09.559219 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000368024 (* 0.0454545 = 1.67283e-05 loss) | |
| I0407 15:25:09.559244 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000360304 (* 0.0454545 = 1.63774e-05 loss) | |
| I0407 15:25:09.559269 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000378336 (* 0.0454545 = 1.71971e-05 loss) | |
| I0407 15:25:09.559291 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:25:09.559311 1004 solver.cpp:245] Train net output #45: total_confidence = 5.51321e-06 | |
| I0407 15:25:09.559353 1004 sgd_solver.cpp:106] Iteration 8000, lr = 0.000984 | |
| I0407 15:25:49.203294 1004 solver.cpp:229] Iteration 8500, loss = 1.09487 | |
| I0407 15:25:49.203450 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 15:25:49.203469 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:25:49.203483 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:25:49.203495 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 15:25:49.203507 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 15:25:49.203519 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 15:25:49.203536 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 15:25:49.203547 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 15:25:49.203559 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:25:49.203572 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:25:49.203583 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:25:49.203594 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:25:49.203606 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:25:49.203618 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:25:49.203629 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:25:49.203640 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:25:49.203651 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:25:49.203662 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:25:49.203673 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:25:49.203685 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:25:49.203696 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:25:49.203708 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:25:49.203723 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.82844 (* 0.0454545 = 0.17402 loss) | |
| I0407 15:25:49.203738 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.74757 (* 0.0454545 = 0.170344 loss) | |
| I0407 15:25:49.203752 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.80373 (* 0.0454545 = 0.172897 loss) | |
| I0407 15:25:49.203765 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.86465 (* 0.0454545 = 0.175666 loss) | |
| I0407 15:25:49.203779 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.79405 (* 0.0454545 = 0.172457 loss) | |
| I0407 15:25:49.203793 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.06686 (* 0.0454545 = 0.139403 loss) | |
| I0407 15:25:49.203806 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.91384 (* 0.0454545 = 0.0869928 loss) | |
| I0407 15:25:49.203820 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.09694 (* 0.0454545 = 0.0498611 loss) | |
| I0407 15:25:49.203835 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.421811 (* 0.0454545 = 0.0191732 loss) | |
| I0407 15:25:49.203848 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.029208 (* 0.0454545 = 0.00132763 loss) | |
| I0407 15:25:49.203863 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.00116584 (* 0.0454545 = 5.29928e-05 loss) | |
| I0407 15:25:49.203877 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.0011636 (* 0.0454545 = 5.28909e-05 loss) | |
| I0407 15:25:49.203891 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.00127692 (* 0.0454545 = 5.80416e-05 loss) | |
| I0407 15:25:49.203905 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00116278 (* 0.0454545 = 5.28538e-05 loss) | |
| I0407 15:25:49.203919 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.0011479 (* 0.0454545 = 5.21774e-05 loss) | |
| I0407 15:25:49.203933 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.00116874 (* 0.0454545 = 5.31245e-05 loss) | |
| I0407 15:25:49.203948 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.00114343 (* 0.0454545 = 5.1974e-05 loss) | |
| I0407 15:25:49.203975 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.00117826 (* 0.0454545 = 5.35571e-05 loss) | |
| I0407 15:25:49.203990 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00117655 (* 0.0454545 = 5.34796e-05 loss) | |
| I0407 15:25:49.204005 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.00119524 (* 0.0454545 = 5.43289e-05 loss) | |
| I0407 15:25:49.204018 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00111161 (* 0.0454545 = 5.05277e-05 loss) | |
| I0407 15:25:49.204033 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00116748 (* 0.0454545 = 5.30674e-05 loss) | |
| I0407 15:25:49.204046 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:25:49.204056 1004 solver.cpp:245] Train net output #45: total_confidence = 2.93008e-07 | |
| I0407 15:25:49.204069 1004 sgd_solver.cpp:106] Iteration 8500, lr = 0.000983 | |
| I0407 15:26:28.684218 1004 solver.cpp:229] Iteration 9000, loss = 1.09459 | |
| I0407 15:26:28.684329 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:26:28.684358 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:26:28.684381 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:26:28.684404 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 15:26:28.684427 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 15:26:28.684448 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.25 | |
| I0407 15:26:28.684469 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 15:26:28.684492 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 15:26:28.684514 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:26:28.684535 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:26:28.684554 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:26:28.684574 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:26:28.684595 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:26:28.684618 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:26:28.684639 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:26:28.684659 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:26:28.684679 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:26:28.684700 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:26:28.684720 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:26:28.684741 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:26:28.684762 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:26:28.684783 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:26:28.684811 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.60862 (* 0.0454545 = 0.164028 loss) | |
| I0407 15:26:28.684837 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.64317 (* 0.0454545 = 0.165599 loss) | |
| I0407 15:26:28.684861 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.93889 (* 0.0454545 = 0.179041 loss) | |
| I0407 15:26:28.684886 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.77286 (* 0.0454545 = 0.171494 loss) | |
| I0407 15:26:28.684911 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.86156 (* 0.0454545 = 0.175526 loss) | |
| I0407 15:26:28.684940 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.19288 (* 0.0454545 = 0.145131 loss) | |
| I0407 15:26:28.684965 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.73092 (* 0.0454545 = 0.0786783 loss) | |
| I0407 15:26:28.684990 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.0756575 (* 0.0454545 = 0.00343898 loss) | |
| I0407 15:26:28.685019 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.029141 (* 0.0454545 = 0.00132459 loss) | |
| I0407 15:26:28.685045 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0118837 (* 0.0454545 = 0.000540166 loss) | |
| I0407 15:26:28.685070 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000351154 (* 0.0454545 = 1.59616e-05 loss) | |
| I0407 15:26:28.685096 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000346263 (* 0.0454545 = 1.57392e-05 loss) | |
| I0407 15:26:28.685122 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000390581 (* 0.0454545 = 1.77537e-05 loss) | |
| I0407 15:26:28.685147 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000376164 (* 0.0454545 = 1.70984e-05 loss) | |
| I0407 15:26:28.685171 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000375957 (* 0.0454545 = 1.70889e-05 loss) | |
| I0407 15:26:28.685196 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000398786 (* 0.0454545 = 1.81267e-05 loss) | |
| I0407 15:26:28.685222 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000365396 (* 0.0454545 = 1.66089e-05 loss) | |
| I0407 15:26:28.685267 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000385949 (* 0.0454545 = 1.75431e-05 loss) | |
| I0407 15:26:28.685295 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000375748 (* 0.0454545 = 1.70795e-05 loss) | |
| I0407 15:26:28.685322 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000332873 (* 0.0454545 = 1.51306e-05 loss) | |
| I0407 15:26:28.685351 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000399072 (* 0.0454545 = 1.81396e-05 loss) | |
| I0407 15:26:28.685376 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000441285 (* 0.0454545 = 2.00584e-05 loss) | |
| I0407 15:26:28.685398 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:26:28.685418 1004 solver.cpp:245] Train net output #45: total_confidence = 1.73255e-06 | |
| I0407 15:26:28.685441 1004 sgd_solver.cpp:106] Iteration 9000, lr = 0.000982 | |
| I0407 15:27:08.015436 1004 solver.cpp:229] Iteration 9500, loss = 1.09398 | |
| I0407 15:27:08.015553 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 15:27:08.015583 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:27:08.015605 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 15:27:08.015627 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 15:27:08.015650 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 15:27:08.015671 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 15:27:08.015692 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 15:27:08.015712 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 15:27:08.015733 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.875 | |
| I0407 15:27:08.015756 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:27:08.015779 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:27:08.015799 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:27:08.015818 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:27:08.015839 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:27:08.015861 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:27:08.015880 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:27:08.015902 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:27:08.015928 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:27:08.015951 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:27:08.015972 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:27:08.015992 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:27:08.016013 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:27:08.016041 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.73353 (* 0.0454545 = 0.169706 loss) | |
| I0407 15:27:08.016067 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.79037 (* 0.0454545 = 0.17229 loss) | |
| I0407 15:27:08.016091 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.89981 (* 0.0454545 = 0.177264 loss) | |
| I0407 15:27:08.016118 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.90103 (* 0.0454545 = 0.17732 loss) | |
| I0407 15:27:08.016144 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.5613 (* 0.0454545 = 0.161877 loss) | |
| I0407 15:27:08.016170 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.2255 (* 0.0454545 = 0.146613 loss) | |
| I0407 15:27:08.016196 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.16602 (* 0.0454545 = 0.053001 loss) | |
| I0407 15:27:08.016221 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.760237 (* 0.0454545 = 0.0345562 loss) | |
| I0407 15:27:08.016245 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.847757 (* 0.0454545 = 0.0385344 loss) | |
| I0407 15:27:08.016270 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0167571 (* 0.0454545 = 0.000761684 loss) | |
| I0407 15:27:08.016296 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000451851 (* 0.0454545 = 2.05387e-05 loss) | |
| I0407 15:27:08.016321 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000441021 (* 0.0454545 = 2.00464e-05 loss) | |
| I0407 15:27:08.016345 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000437482 (* 0.0454545 = 1.98855e-05 loss) | |
| I0407 15:27:08.016371 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000427163 (* 0.0454545 = 1.94165e-05 loss) | |
| I0407 15:27:08.016397 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000462041 (* 0.0454545 = 2.10019e-05 loss) | |
| I0407 15:27:08.016424 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000429756 (* 0.0454545 = 1.95344e-05 loss) | |
| I0407 15:27:08.016449 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000473276 (* 0.0454545 = 2.15125e-05 loss) | |
| I0407 15:27:08.016496 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000465361 (* 0.0454545 = 2.11528e-05 loss) | |
| I0407 15:27:08.016522 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000439633 (* 0.0454545 = 1.99833e-05 loss) | |
| I0407 15:27:08.016546 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000463856 (* 0.0454545 = 2.10843e-05 loss) | |
| I0407 15:27:08.016576 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000458544 (* 0.0454545 = 2.08429e-05 loss) | |
| I0407 15:27:08.016602 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000443083 (* 0.0454545 = 2.01402e-05 loss) | |
| I0407 15:27:08.016623 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:27:08.016644 1004 solver.cpp:245] Train net output #45: total_confidence = 8.18007e-06 | |
| I0407 15:27:08.016664 1004 sgd_solver.cpp:106] Iteration 9500, lr = 0.000981 | |
| I0407 15:27:46.077646 1004 solver.cpp:338] Iteration 10000, Testing net (#0) | |
| I0407 15:27:53.973971 1004 solver.cpp:393] Test loss: 0.969817 | |
| I0407 15:27:53.974019 1004 solver.cpp:406] Test net output #0: loss/accuracy01 = 0 | |
| I0407 15:27:53.974046 1004 solver.cpp:406] Test net output #1: loss/accuracy02 = 0.124 | |
| I0407 15:27:53.974069 1004 solver.cpp:406] Test net output #2: loss/accuracy03 = 0.081 | |
| I0407 15:27:53.974093 1004 solver.cpp:406] Test net output #3: loss/accuracy04 = 0.09 | |
| I0407 15:27:53.974115 1004 solver.cpp:406] Test net output #4: loss/accuracy05 = 0.213 | |
| I0407 15:27:53.974135 1004 solver.cpp:406] Test net output #5: loss/accuracy06 = 0.502 | |
| I0407 15:27:53.974156 1004 solver.cpp:406] Test net output #6: loss/accuracy07 = 0.894 | |
| I0407 15:27:53.974177 1004 solver.cpp:406] Test net output #7: loss/accuracy08 = 0.97 | |
| I0407 15:27:53.974197 1004 solver.cpp:406] Test net output #8: loss/accuracy09 = 0.995 | |
| I0407 15:27:53.974217 1004 solver.cpp:406] Test net output #9: loss/accuracy10 = 0.998 | |
| I0407 15:27:53.974237 1004 solver.cpp:406] Test net output #10: loss/accuracy11 = 1 | |
| I0407 15:27:53.974258 1004 solver.cpp:406] Test net output #11: loss/accuracy12 = 1 | |
| I0407 15:27:53.974280 1004 solver.cpp:406] Test net output #12: loss/accuracy13 = 1 | |
| I0407 15:27:53.974301 1004 solver.cpp:406] Test net output #13: loss/accuracy14 = 1 | |
| I0407 15:27:53.974320 1004 solver.cpp:406] Test net output #14: loss/accuracy15 = 1 | |
| I0407 15:27:53.974339 1004 solver.cpp:406] Test net output #15: loss/accuracy16 = 1 | |
| I0407 15:27:53.974359 1004 solver.cpp:406] Test net output #16: loss/accuracy17 = 1 | |
| I0407 15:27:53.974378 1004 solver.cpp:406] Test net output #17: loss/accuracy18 = 1 | |
| I0407 15:27:53.974397 1004 solver.cpp:406] Test net output #18: loss/accuracy19 = 1 | |
| I0407 15:27:53.974417 1004 solver.cpp:406] Test net output #19: loss/accuracy20 = 1 | |
| I0407 15:27:53.974437 1004 solver.cpp:406] Test net output #20: loss/accuracy21 = 1 | |
| I0407 15:27:53.974458 1004 solver.cpp:406] Test net output #21: loss/accuracy22 = 1 | |
| I0407 15:27:53.974485 1004 solver.cpp:406] Test net output #22: loss/loss01 = 3.30996 (* 0.0454545 = 0.150453 loss) | |
| I0407 15:27:53.974511 1004 solver.cpp:406] Test net output #23: loss/loss02 = 3.50193 (* 0.0454545 = 0.159178 loss) | |
| I0407 15:27:53.974535 1004 solver.cpp:406] Test net output #24: loss/loss03 = 3.60704 (* 0.0454545 = 0.163956 loss) | |
| I0407 15:27:53.974560 1004 solver.cpp:406] Test net output #25: loss/loss04 = 3.63403 (* 0.0454545 = 0.165183 loss) | |
| I0407 15:27:53.974583 1004 solver.cpp:406] Test net output #26: loss/loss05 = 3.52901 (* 0.0454545 = 0.16041 loss) | |
| I0407 15:27:53.974607 1004 solver.cpp:406] Test net output #27: loss/loss06 = 2.45808 (* 0.0454545 = 0.111731 loss) | |
| I0407 15:27:53.974632 1004 solver.cpp:406] Test net output #28: loss/loss07 = 0.837081 (* 0.0454545 = 0.0380491 loss) | |
| I0407 15:27:53.974655 1004 solver.cpp:406] Test net output #29: loss/loss08 = 0.316383 (* 0.0454545 = 0.014381 loss) | |
| I0407 15:27:53.974683 1004 solver.cpp:406] Test net output #30: loss/loss09 = 0.0850535 (* 0.0454545 = 0.00386607 loss) | |
| I0407 15:27:53.974709 1004 solver.cpp:406] Test net output #31: loss/loss10 = 0.037544 (* 0.0454545 = 0.00170654 loss) | |
| I0407 15:27:53.974733 1004 solver.cpp:406] Test net output #32: loss/loss11 = 0.0016655 (* 0.0454545 = 7.57047e-05 loss) | |
| I0407 15:27:53.974758 1004 solver.cpp:406] Test net output #33: loss/loss12 = 0.00164217 (* 0.0454545 = 7.4644e-05 loss) | |
| I0407 15:27:53.974782 1004 solver.cpp:406] Test net output #34: loss/loss13 = 0.00165233 (* 0.0454545 = 7.51057e-05 loss) | |
| I0407 15:27:53.974807 1004 solver.cpp:406] Test net output #35: loss/loss14 = 0.00165471 (* 0.0454545 = 7.52142e-05 loss) | |
| I0407 15:27:53.974834 1004 solver.cpp:406] Test net output #36: loss/loss15 = 0.00166338 (* 0.0454545 = 7.56083e-05 loss) | |
| I0407 15:27:53.974860 1004 solver.cpp:406] Test net output #37: loss/loss16 = 0.00166275 (* 0.0454545 = 7.55796e-05 loss) | |
| I0407 15:27:53.974884 1004 solver.cpp:406] Test net output #38: loss/loss17 = 0.00165201 (* 0.0454545 = 7.50912e-05 loss) | |
| I0407 15:27:53.974947 1004 solver.cpp:406] Test net output #39: loss/loss18 = 0.00165673 (* 0.0454545 = 7.5306e-05 loss) | |
| I0407 15:27:53.974978 1004 solver.cpp:406] Test net output #40: loss/loss19 = 0.00165616 (* 0.0454545 = 7.528e-05 loss) | |
| I0407 15:27:53.975005 1004 solver.cpp:406] Test net output #41: loss/loss20 = 0.00166249 (* 0.0454545 = 7.55677e-05 loss) | |
| I0407 15:27:53.975029 1004 solver.cpp:406] Test net output #42: loss/loss21 = 0.00166385 (* 0.0454545 = 7.56295e-05 loss) | |
| I0407 15:27:53.975054 1004 solver.cpp:406] Test net output #43: loss/loss22 = 0.00165271 (* 0.0454545 = 7.51232e-05 loss) | |
| I0407 15:27:53.975075 1004 solver.cpp:406] Test net output #44: total_accuracy = 0 | |
| I0407 15:27:53.975095 1004 solver.cpp:406] Test net output #45: total_confidence = 9.78676e-06 | |
| I0407 15:27:53.997715 1004 solver.cpp:229] Iteration 10000, loss = 1.0963 | |
| I0407 15:27:53.997756 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.1875 | |
| I0407 15:27:53.997774 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:27:53.997787 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 15:27:53.997800 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 15:27:53.997812 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 15:27:53.997824 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5625 | |
| I0407 15:27:53.997836 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.875 | |
| I0407 15:27:53.997848 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 15:27:53.997860 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:27:53.997874 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:27:53.997884 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:27:53.997896 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:27:53.997912 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:27:53.997925 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:27:53.997936 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:27:53.997947 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:27:53.997959 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:27:53.997972 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:27:53.997983 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:27:53.997994 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:27:53.998006 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:27:53.998018 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:27:53.998033 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.51818 (* 0.0454545 = 0.159917 loss) | |
| I0407 15:27:53.998046 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.45476 (* 0.0454545 = 0.157034 loss) | |
| I0407 15:27:53.998060 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.78767 (* 0.0454545 = 0.172167 loss) | |
| I0407 15:27:53.998076 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.61615 (* 0.0454545 = 0.164371 loss) | |
| I0407 15:27:53.998091 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.50877 (* 0.0454545 = 0.159489 loss) | |
| I0407 15:27:53.998106 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.21312 (* 0.0454545 = 0.100596 loss) | |
| I0407 15:27:53.998119 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.743894 (* 0.0454545 = 0.0338133 loss) | |
| I0407 15:27:53.998133 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.399739 (* 0.0454545 = 0.0181699 loss) | |
| I0407 15:27:53.998147 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.00872509 (* 0.0454545 = 0.000396595 loss) | |
| I0407 15:27:53.998162 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.00249332 (* 0.0454545 = 0.000113333 loss) | |
| I0407 15:27:53.998194 1004 solver.cpp:245] Train net output #32: loss/loss11 = 2.27997e-05 (* 0.0454545 = 1.03635e-06 loss) | |
| I0407 15:27:53.998210 1004 solver.cpp:245] Train net output #33: loss/loss12 = 2.19427e-05 (* 0.0454545 = 9.97397e-07 loss) | |
| I0407 15:27:53.998224 1004 solver.cpp:245] Train net output #34: loss/loss13 = 2.24047e-05 (* 0.0454545 = 1.0184e-06 loss) | |
| I0407 15:27:53.998239 1004 solver.cpp:245] Train net output #35: loss/loss14 = 2.26059e-05 (* 0.0454545 = 1.02754e-06 loss) | |
| I0407 15:27:53.998253 1004 solver.cpp:245] Train net output #36: loss/loss15 = 2.17788e-05 (* 0.0454545 = 9.89946e-07 loss) | |
| I0407 15:27:53.998267 1004 solver.cpp:245] Train net output #37: loss/loss16 = 2.11157e-05 (* 0.0454545 = 9.59803e-07 loss) | |
| I0407 15:27:53.998281 1004 solver.cpp:245] Train net output #38: loss/loss17 = 2.23452e-05 (* 0.0454545 = 1.01569e-06 loss) | |
| I0407 15:27:53.998296 1004 solver.cpp:245] Train net output #39: loss/loss18 = 2.26879e-05 (* 0.0454545 = 1.03127e-06 loss) | |
| I0407 15:27:53.998309 1004 solver.cpp:245] Train net output #40: loss/loss19 = 2.19054e-05 (* 0.0454545 = 9.95702e-07 loss) | |
| I0407 15:27:53.998323 1004 solver.cpp:245] Train net output #41: loss/loss20 = 2.22408e-05 (* 0.0454545 = 1.01095e-06 loss) | |
| I0407 15:27:53.998337 1004 solver.cpp:245] Train net output #42: loss/loss21 = 2.23377e-05 (* 0.0454545 = 1.01535e-06 loss) | |
| I0407 15:27:53.998350 1004 solver.cpp:245] Train net output #43: loss/loss22 = 2.29114e-05 (* 0.0454545 = 1.04143e-06 loss) | |
| I0407 15:27:53.998363 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:27:53.998374 1004 solver.cpp:245] Train net output #45: total_confidence = 1.14637e-05 | |
| I0407 15:27:53.998389 1004 sgd_solver.cpp:106] Iteration 10000, lr = 0.00098 | |
| I0407 15:28:31.569602 1004 solver.cpp:229] Iteration 10500, loss = 1.09612 | |
| I0407 15:28:31.569736 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 15:28:31.569764 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:28:31.569790 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:28:31.569811 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 15:28:31.569833 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 15:28:31.569854 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 15:28:31.569876 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 15:28:31.569897 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 15:28:31.569917 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:28:31.569937 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:28:31.569957 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:28:31.569977 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:28:31.569998 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:28:31.570020 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:28:31.570041 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:28:31.570062 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:28:31.570086 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:28:31.570107 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:28:31.570127 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:28:31.570147 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:28:31.570166 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:28:31.570186 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:28:31.570214 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.69875 (* 0.0454545 = 0.168125 loss) | |
| I0407 15:28:31.570241 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.65319 (* 0.0454545 = 0.166054 loss) | |
| I0407 15:28:31.570267 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.62987 (* 0.0454545 = 0.164994 loss) | |
| I0407 15:28:31.570291 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.74295 (* 0.0454545 = 0.170134 loss) | |
| I0407 15:28:31.570317 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.15689 (* 0.0454545 = 0.143495 loss) | |
| I0407 15:28:31.570340 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.91263 (* 0.0454545 = 0.132392 loss) | |
| I0407 15:28:31.570365 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.44246 (* 0.0454545 = 0.0655661 loss) | |
| I0407 15:28:31.570391 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.0694791 (* 0.0454545 = 0.00315814 loss) | |
| I0407 15:28:31.570416 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.025751 (* 0.0454545 = 0.0011705 loss) | |
| I0407 15:28:31.570442 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.00836088 (* 0.0454545 = 0.00038004 loss) | |
| I0407 15:28:31.570467 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000153795 (* 0.0454545 = 6.9907e-06 loss) | |
| I0407 15:28:31.570494 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000143761 (* 0.0454545 = 6.53457e-06 loss) | |
| I0407 15:28:31.570523 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000157242 (* 0.0454545 = 7.14739e-06 loss) | |
| I0407 15:28:31.570547 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000154476 (* 0.0454545 = 7.02164e-06 loss) | |
| I0407 15:28:31.570571 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000145692 (* 0.0454545 = 6.62236e-06 loss) | |
| I0407 15:28:31.570596 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000138153 (* 0.0454545 = 6.2797e-06 loss) | |
| I0407 15:28:31.570621 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000151246 (* 0.0454545 = 6.8748e-06 loss) | |
| I0407 15:28:31.570664 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000140403 (* 0.0454545 = 6.38195e-06 loss) | |
| I0407 15:28:31.570690 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000156051 (* 0.0454545 = 7.09322e-06 loss) | |
| I0407 15:28:31.570715 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000143611 (* 0.0454545 = 6.52777e-06 loss) | |
| I0407 15:28:31.570739 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000149619 (* 0.0454545 = 6.80087e-06 loss) | |
| I0407 15:28:31.570763 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00015472 (* 0.0454545 = 7.03273e-06 loss) | |
| I0407 15:28:31.570785 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:28:31.570806 1004 solver.cpp:245] Train net output #45: total_confidence = 8.56367e-06 | |
| I0407 15:28:31.570830 1004 sgd_solver.cpp:106] Iteration 10500, lr = 0.000979 | |
| I0407 15:29:09.542266 1004 solver.cpp:229] Iteration 11000, loss = 1.09345 | |
| I0407 15:29:09.542367 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:29:09.542397 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:29:09.542419 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 15:29:09.542441 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 15:29:09.542464 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 15:29:09.542484 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 15:29:09.542505 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 15:29:09.542526 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 15:29:09.542548 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:29:09.542570 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:29:09.542590 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:29:09.542610 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:29:09.542630 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:29:09.542650 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:29:09.542671 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:29:09.542693 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:29:09.542716 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:29:09.542737 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:29:09.542758 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:29:09.542778 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:29:09.542799 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:29:09.542820 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:29:09.542846 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.44834 (* 0.0454545 = 0.156743 loss) | |
| I0407 15:29:09.542872 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.67013 (* 0.0454545 = 0.166824 loss) | |
| I0407 15:29:09.542898 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.76013 (* 0.0454545 = 0.170915 loss) | |
| I0407 15:29:09.542925 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.70147 (* 0.0454545 = 0.168249 loss) | |
| I0407 15:29:09.542951 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.27998 (* 0.0454545 = 0.14909 loss) | |
| I0407 15:29:09.542978 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.85065 (* 0.0454545 = 0.129575 loss) | |
| I0407 15:29:09.543002 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.16943 (* 0.0454545 = 0.0531561 loss) | |
| I0407 15:29:09.543027 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.713789 (* 0.0454545 = 0.032445 loss) | |
| I0407 15:29:09.543052 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0376856 (* 0.0454545 = 0.00171298 loss) | |
| I0407 15:29:09.543082 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0166576 (* 0.0454545 = 0.000757165 loss) | |
| I0407 15:29:09.543108 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000361706 (* 0.0454545 = 1.64412e-05 loss) | |
| I0407 15:29:09.543134 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000344175 (* 0.0454545 = 1.56443e-05 loss) | |
| I0407 15:29:09.543161 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000377938 (* 0.0454545 = 1.7179e-05 loss) | |
| I0407 15:29:09.543189 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000364827 (* 0.0454545 = 1.6583e-05 loss) | |
| I0407 15:29:09.543213 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000384125 (* 0.0454545 = 1.74602e-05 loss) | |
| I0407 15:29:09.543239 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000359624 (* 0.0454545 = 1.63466e-05 loss) | |
| I0407 15:29:09.543264 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000377954 (* 0.0454545 = 1.71797e-05 loss) | |
| I0407 15:29:09.543311 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.00036187 (* 0.0454545 = 1.64486e-05 loss) | |
| I0407 15:29:09.543359 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00034919 (* 0.0454545 = 1.58723e-05 loss) | |
| I0407 15:29:09.543391 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000366924 (* 0.0454545 = 1.66784e-05 loss) | |
| I0407 15:29:09.543417 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000382079 (* 0.0454545 = 1.73672e-05 loss) | |
| I0407 15:29:09.543442 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000386835 (* 0.0454545 = 1.75834e-05 loss) | |
| I0407 15:29:09.543463 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:29:09.543483 1004 solver.cpp:245] Train net output #45: total_confidence = 7.10282e-06 | |
| I0407 15:29:09.543506 1004 sgd_solver.cpp:106] Iteration 11000, lr = 0.000978 | |
| I0407 15:29:47.712546 1004 solver.cpp:229] Iteration 11500, loss = 1.09773 | |
| I0407 15:29:47.712643 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:29:47.712662 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:29:47.712676 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:29:47.712687 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 15:29:47.712700 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 15:29:47.712713 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 15:29:47.712724 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.9375 | |
| I0407 15:29:47.712736 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 15:29:47.712749 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:29:47.712760 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:29:47.712771 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:29:47.712784 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:29:47.712795 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:29:47.712807 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:29:47.712818 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:29:47.712831 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:29:47.712841 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:29:47.712853 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:29:47.712864 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:29:47.712875 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:29:47.712888 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:29:47.712899 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:29:47.712914 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.58224 (* 0.0454545 = 0.162829 loss) | |
| I0407 15:29:47.712929 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.72177 (* 0.0454545 = 0.169171 loss) | |
| I0407 15:29:47.712944 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.99654 (* 0.0454545 = 0.181661 loss) | |
| I0407 15:29:47.712956 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.78533 (* 0.0454545 = 0.17206 loss) | |
| I0407 15:29:47.712970 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.63707 (* 0.0454545 = 0.165321 loss) | |
| I0407 15:29:47.712985 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.9199 (* 0.0454545 = 0.132723 loss) | |
| I0407 15:29:47.712997 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.828649 (* 0.0454545 = 0.0376659 loss) | |
| I0407 15:29:47.713011 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.0934685 (* 0.0454545 = 0.00424857 loss) | |
| I0407 15:29:47.713027 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0352727 (* 0.0454545 = 0.00160331 loss) | |
| I0407 15:29:47.713040 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0128182 (* 0.0454545 = 0.000582643 loss) | |
| I0407 15:29:47.713054 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000324931 (* 0.0454545 = 1.47696e-05 loss) | |
| I0407 15:29:47.713069 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000308367 (* 0.0454545 = 1.40167e-05 loss) | |
| I0407 15:29:47.713086 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000316296 (* 0.0454545 = 1.43771e-05 loss) | |
| I0407 15:29:47.713101 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000326114 (* 0.0454545 = 1.48234e-05 loss) | |
| I0407 15:29:47.713115 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000333029 (* 0.0454545 = 1.51377e-05 loss) | |
| I0407 15:29:47.713129 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000318595 (* 0.0454545 = 1.44816e-05 loss) | |
| I0407 15:29:47.713143 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000313022 (* 0.0454545 = 1.42283e-05 loss) | |
| I0407 15:29:47.713174 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000327026 (* 0.0454545 = 1.48648e-05 loss) | |
| I0407 15:29:47.713189 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000322194 (* 0.0454545 = 1.46452e-05 loss) | |
| I0407 15:29:47.713203 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.00031676 (* 0.0454545 = 1.43982e-05 loss) | |
| I0407 15:29:47.713217 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000330045 (* 0.0454545 = 1.5002e-05 loss) | |
| I0407 15:29:47.713232 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000309283 (* 0.0454545 = 1.40583e-05 loss) | |
| I0407 15:29:47.713243 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:29:47.713255 1004 solver.cpp:245] Train net output #45: total_confidence = 2.45776e-06 | |
| I0407 15:29:47.713268 1004 sgd_solver.cpp:106] Iteration 11500, lr = 0.000977 | |
| I0407 15:30:25.647348 1004 solver.cpp:229] Iteration 12000, loss = 1.0944 | |
| I0407 15:30:25.647470 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 15:30:25.647490 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.125 | |
| I0407 15:30:25.647503 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:30:25.647516 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 15:30:25.647528 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 15:30:25.647547 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 15:30:25.647559 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 15:30:25.647572 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 15:30:25.647583 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.875 | |
| I0407 15:30:25.647595 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.875 | |
| I0407 15:30:25.647608 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:30:25.647619 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:30:25.647631 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:30:25.647644 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:30:25.647655 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:30:25.647667 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:30:25.647680 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:30:25.647691 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:30:25.647702 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:30:25.647714 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:30:25.647725 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:30:25.647737 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:30:25.647753 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.54604 (* 0.0454545 = 0.161184 loss) | |
| I0407 15:30:25.647768 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.62753 (* 0.0454545 = 0.164888 loss) | |
| I0407 15:30:25.647783 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.87022 (* 0.0454545 = 0.175919 loss) | |
| I0407 15:30:25.647796 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.76569 (* 0.0454545 = 0.171168 loss) | |
| I0407 15:30:25.647809 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.51177 (* 0.0454545 = 0.159626 loss) | |
| I0407 15:30:25.647824 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.98855 (* 0.0454545 = 0.135843 loss) | |
| I0407 15:30:25.647837 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.51265 (* 0.0454545 = 0.0687569 loss) | |
| I0407 15:30:25.647851 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.0238 (* 0.0454545 = 0.0465363 loss) | |
| I0407 15:30:25.647864 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.711869 (* 0.0454545 = 0.0323577 loss) | |
| I0407 15:30:25.647878 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.778248 (* 0.0454545 = 0.0353749 loss) | |
| I0407 15:30:25.647892 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000832462 (* 0.0454545 = 3.78392e-05 loss) | |
| I0407 15:30:25.647908 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000853709 (* 0.0454545 = 3.8805e-05 loss) | |
| I0407 15:30:25.647923 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000902312 (* 0.0454545 = 4.10142e-05 loss) | |
| I0407 15:30:25.647938 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000861424 (* 0.0454545 = 3.91556e-05 loss) | |
| I0407 15:30:25.647951 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000820628 (* 0.0454545 = 3.73013e-05 loss) | |
| I0407 15:30:25.647965 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000843624 (* 0.0454545 = 3.83465e-05 loss) | |
| I0407 15:30:25.647979 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000899223 (* 0.0454545 = 4.08738e-05 loss) | |
| I0407 15:30:25.648006 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000812421 (* 0.0454545 = 3.69282e-05 loss) | |
| I0407 15:30:25.648022 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000832213 (* 0.0454545 = 3.78278e-05 loss) | |
| I0407 15:30:25.648036 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000879584 (* 0.0454545 = 3.99811e-05 loss) | |
| I0407 15:30:25.648049 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000833067 (* 0.0454545 = 3.78667e-05 loss) | |
| I0407 15:30:25.648063 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000783768 (* 0.0454545 = 3.56258e-05 loss) | |
| I0407 15:30:25.648078 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:30:25.648090 1004 solver.cpp:245] Train net output #45: total_confidence = 6.10795e-06 | |
| I0407 15:30:25.648104 1004 sgd_solver.cpp:106] Iteration 12000, lr = 0.000976 | |
| I0407 15:31:04.499168 1004 solver.cpp:229] Iteration 12500, loss = 1.09019 | |
| I0407 15:31:04.499274 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:31:04.499302 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:31:04.499351 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:31:04.499377 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 15:31:04.499397 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 15:31:04.499419 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 15:31:04.499441 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 15:31:04.499464 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 15:31:04.499485 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:31:04.499505 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:31:04.499526 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:31:04.499548 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:31:04.499569 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:31:04.499589 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:31:04.499610 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:31:04.499630 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:31:04.499651 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:31:04.499672 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:31:04.499694 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:31:04.499716 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:31:04.499737 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:31:04.499758 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:31:04.499783 1004 solver.cpp:245] Train net output #22: loss/loss01 = 4.04793 (* 0.0454545 = 0.183997 loss) | |
| I0407 15:31:04.499809 1004 solver.cpp:245] Train net output #23: loss/loss02 = 4.10752 (* 0.0454545 = 0.186706 loss) | |
| I0407 15:31:04.499833 1004 solver.cpp:245] Train net output #24: loss/loss03 = 4.27085 (* 0.0454545 = 0.19413 loss) | |
| I0407 15:31:04.499860 1004 solver.cpp:245] Train net output #25: loss/loss04 = 4.00999 (* 0.0454545 = 0.182273 loss) | |
| I0407 15:31:04.499886 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.70865 (* 0.0454545 = 0.168575 loss) | |
| I0407 15:31:04.499912 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.01634 (* 0.0454545 = 0.137107 loss) | |
| I0407 15:31:04.499943 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.86461 (* 0.0454545 = 0.0847548 loss) | |
| I0407 15:31:04.499969 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.16664 (* 0.0454545 = 0.0530292 loss) | |
| I0407 15:31:04.499992 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.494074 (* 0.0454545 = 0.0224579 loss) | |
| I0407 15:31:04.500018 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0418341 (* 0.0454545 = 0.00190155 loss) | |
| I0407 15:31:04.500044 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.00157343 (* 0.0454545 = 7.15196e-05 loss) | |
| I0407 15:31:04.500069 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00163865 (* 0.0454545 = 7.44842e-05 loss) | |
| I0407 15:31:04.500094 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.00165555 (* 0.0454545 = 7.52524e-05 loss) | |
| I0407 15:31:04.500119 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00167285 (* 0.0454545 = 7.60388e-05 loss) | |
| I0407 15:31:04.500145 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.00167541 (* 0.0454545 = 7.61551e-05 loss) | |
| I0407 15:31:04.500172 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.00167719 (* 0.0454545 = 7.6236e-05 loss) | |
| I0407 15:31:04.500198 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.00160697 (* 0.0454545 = 7.30439e-05 loss) | |
| I0407 15:31:04.500244 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.00168946 (* 0.0454545 = 7.67937e-05 loss) | |
| I0407 15:31:04.500270 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00164707 (* 0.0454545 = 7.48668e-05 loss) | |
| I0407 15:31:04.500300 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.00163487 (* 0.0454545 = 7.43122e-05 loss) | |
| I0407 15:31:04.500326 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.0016789 (* 0.0454545 = 7.63134e-05 loss) | |
| I0407 15:31:04.500352 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00168401 (* 0.0454545 = 7.6546e-05 loss) | |
| I0407 15:31:04.500373 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:31:04.500393 1004 solver.cpp:245] Train net output #45: total_confidence = 6.09808e-06 | |
| I0407 15:31:04.500416 1004 sgd_solver.cpp:106] Iteration 12500, lr = 0.000975 | |
| I0407 15:31:42.602500 1004 solver.cpp:229] Iteration 13000, loss = 1.09407 | |
| I0407 15:31:42.602602 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:31:42.602625 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:31:42.602638 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 15:31:42.602651 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 15:31:42.602663 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.3125 | |
| I0407 15:31:42.602676 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5 | |
| I0407 15:31:42.602687 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 15:31:42.602699 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 15:31:42.602711 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:31:42.602723 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:31:42.602735 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:31:42.602746 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:31:42.602758 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:31:42.602769 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:31:42.602782 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:31:42.602793 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:31:42.602805 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:31:42.602816 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:31:42.602828 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:31:42.602839 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:31:42.602851 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:31:42.602862 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:31:42.602877 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.76973 (* 0.0454545 = 0.171351 loss) | |
| I0407 15:31:42.602892 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.62598 (* 0.0454545 = 0.164817 loss) | |
| I0407 15:31:42.602905 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.75102 (* 0.0454545 = 0.170501 loss) | |
| I0407 15:31:42.602919 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.50008 (* 0.0454545 = 0.159095 loss) | |
| I0407 15:31:42.602933 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.21216 (* 0.0454545 = 0.146007 loss) | |
| I0407 15:31:42.602947 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.6613 (* 0.0454545 = 0.120968 loss) | |
| I0407 15:31:42.602962 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.50505 (* 0.0454545 = 0.0684113 loss) | |
| I0407 15:31:42.602974 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.702977 (* 0.0454545 = 0.0319535 loss) | |
| I0407 15:31:42.602988 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0522734 (* 0.0454545 = 0.00237606 loss) | |
| I0407 15:31:42.603003 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0215582 (* 0.0454545 = 0.000979918 loss) | |
| I0407 15:31:42.603018 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000437222 (* 0.0454545 = 1.98737e-05 loss) | |
| I0407 15:31:42.603031 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000417766 (* 0.0454545 = 1.89894e-05 loss) | |
| I0407 15:31:42.603045 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000416915 (* 0.0454545 = 1.89507e-05 loss) | |
| I0407 15:31:42.603060 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000431301 (* 0.0454545 = 1.96046e-05 loss) | |
| I0407 15:31:42.603076 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.0004152 (* 0.0454545 = 1.88727e-05 loss) | |
| I0407 15:31:42.603091 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000403435 (* 0.0454545 = 1.8338e-05 loss) | |
| I0407 15:31:42.603106 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000431892 (* 0.0454545 = 1.96315e-05 loss) | |
| I0407 15:31:42.603137 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000445742 (* 0.0454545 = 2.0261e-05 loss) | |
| I0407 15:31:42.603152 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000421999 (* 0.0454545 = 1.91818e-05 loss) | |
| I0407 15:31:42.603165 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000416329 (* 0.0454545 = 1.89241e-05 loss) | |
| I0407 15:31:42.603179 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000419328 (* 0.0454545 = 1.90604e-05 loss) | |
| I0407 15:31:42.603193 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000424685 (* 0.0454545 = 1.93039e-05 loss) | |
| I0407 15:31:42.603205 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:31:42.603217 1004 solver.cpp:245] Train net output #45: total_confidence = 3.88157e-06 | |
| I0407 15:31:42.603230 1004 sgd_solver.cpp:106] Iteration 13000, lr = 0.000974 | |
| I0407 15:32:20.470170 1004 solver.cpp:229] Iteration 13500, loss = 1.09126 | |
| I0407 15:32:20.470274 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 15:32:20.470304 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:32:20.470326 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:32:20.470360 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 15:32:20.470394 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.0625 | |
| I0407 15:32:20.470417 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 15:32:20.470438 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.5 | |
| I0407 15:32:20.470458 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 15:32:20.470480 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:32:20.470502 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:32:20.470522 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:32:20.470542 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:32:20.470563 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:32:20.470583 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:32:20.470603 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:32:20.470625 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:32:20.470649 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:32:20.470669 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:32:20.470686 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:32:20.470706 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:32:20.470727 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:32:20.470748 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:32:20.470774 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.77924 (* 0.0454545 = 0.171784 loss) | |
| I0407 15:32:20.470800 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.87938 (* 0.0454545 = 0.176335 loss) | |
| I0407 15:32:20.470825 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.87542 (* 0.0454545 = 0.176155 loss) | |
| I0407 15:32:20.470850 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.9184 (* 0.0454545 = 0.178109 loss) | |
| I0407 15:32:20.470876 1004 solver.cpp:245] Train net output #26: loss/loss05 = 4.03897 (* 0.0454545 = 0.18359 loss) | |
| I0407 15:32:20.470902 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.18887 (* 0.0454545 = 0.144949 loss) | |
| I0407 15:32:20.470928 1004 solver.cpp:245] Train net output #28: loss/loss07 = 2.49504 (* 0.0454545 = 0.113411 loss) | |
| I0407 15:32:20.470954 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.09797 (* 0.0454545 = 0.0499075 loss) | |
| I0407 15:32:20.470978 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.53564 (* 0.0454545 = 0.0243473 loss) | |
| I0407 15:32:20.471004 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0329046 (* 0.0454545 = 0.00149566 loss) | |
| I0407 15:32:20.471029 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.00154386 (* 0.0454545 = 7.01756e-05 loss) | |
| I0407 15:32:20.471055 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00147897 (* 0.0454545 = 6.72259e-05 loss) | |
| I0407 15:32:20.471084 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.00158716 (* 0.0454545 = 7.21435e-05 loss) | |
| I0407 15:32:20.471110 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00163997 (* 0.0454545 = 7.45442e-05 loss) | |
| I0407 15:32:20.471135 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.0015397 (* 0.0454545 = 6.99865e-05 loss) | |
| I0407 15:32:20.471161 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.00153874 (* 0.0454545 = 6.99428e-05 loss) | |
| I0407 15:32:20.471186 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.00156802 (* 0.0454545 = 7.12737e-05 loss) | |
| I0407 15:32:20.471233 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.00159929 (* 0.0454545 = 7.26949e-05 loss) | |
| I0407 15:32:20.471261 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00159611 (* 0.0454545 = 7.25505e-05 loss) | |
| I0407 15:32:20.471287 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.00149187 (* 0.0454545 = 6.78121e-05 loss) | |
| I0407 15:32:20.471312 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.0015883 (* 0.0454545 = 7.21953e-05 loss) | |
| I0407 15:32:20.471354 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00154684 (* 0.0454545 = 7.0311e-05 loss) | |
| I0407 15:32:20.471376 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:32:20.471401 1004 solver.cpp:245] Train net output #45: total_confidence = 1.47773e-05 | |
| I0407 15:32:20.471424 1004 sgd_solver.cpp:106] Iteration 13500, lr = 0.000973 | |
| I0407 15:32:58.469681 1004 solver.cpp:229] Iteration 14000, loss = 1.09014 | |
| I0407 15:32:58.469801 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 15:32:58.469830 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:32:58.469856 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 15:32:58.469885 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 15:32:58.469907 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 15:32:58.469929 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 15:32:58.469954 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 15:32:58.469976 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 15:32:58.469997 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:32:58.470018 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:32:58.470039 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:32:58.470059 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:32:58.470085 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:32:58.470108 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:32:58.470129 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:32:58.470150 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:32:58.470171 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:32:58.470191 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:32:58.470212 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:32:58.470232 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:32:58.470254 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:32:58.470278 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:32:58.470304 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.82927 (* 0.0454545 = 0.174058 loss) | |
| I0407 15:32:58.470331 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.84323 (* 0.0454545 = 0.174692 loss) | |
| I0407 15:32:58.470356 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.83099 (* 0.0454545 = 0.174136 loss) | |
| I0407 15:32:58.470382 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.54443 (* 0.0454545 = 0.16111 loss) | |
| I0407 15:32:58.470407 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.64535 (* 0.0454545 = 0.165698 loss) | |
| I0407 15:32:58.470432 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.8695 (* 0.0454545 = 0.130432 loss) | |
| I0407 15:32:58.470456 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.76677 (* 0.0454545 = 0.0803078 loss) | |
| I0407 15:32:58.470482 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.500451 (* 0.0454545 = 0.0227478 loss) | |
| I0407 15:32:58.470509 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.447555 (* 0.0454545 = 0.0203434 loss) | |
| I0407 15:32:58.470535 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0326539 (* 0.0454545 = 0.00148427 loss) | |
| I0407 15:32:58.470561 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.00126291 (* 0.0454545 = 5.74051e-05 loss) | |
| I0407 15:32:58.470587 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00127978 (* 0.0454545 = 5.81716e-05 loss) | |
| I0407 15:32:58.470613 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.00127716 (* 0.0454545 = 5.80528e-05 loss) | |
| I0407 15:32:58.470638 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00124038 (* 0.0454545 = 5.6381e-05 loss) | |
| I0407 15:32:58.470662 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.00136144 (* 0.0454545 = 6.18834e-05 loss) | |
| I0407 15:32:58.470688 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.00130054 (* 0.0454545 = 5.91154e-05 loss) | |
| I0407 15:32:58.470713 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.00132282 (* 0.0454545 = 6.01284e-05 loss) | |
| I0407 15:32:58.470757 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.00129568 (* 0.0454545 = 5.88944e-05 loss) | |
| I0407 15:32:58.470784 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00132937 (* 0.0454545 = 6.04258e-05 loss) | |
| I0407 15:32:58.470811 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.00133025 (* 0.0454545 = 6.04657e-05 loss) | |
| I0407 15:32:58.470837 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00135896 (* 0.0454545 = 6.1771e-05 loss) | |
| I0407 15:32:58.470865 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00128273 (* 0.0454545 = 5.83059e-05 loss) | |
| I0407 15:32:58.470885 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:32:58.470906 1004 solver.cpp:245] Train net output #45: total_confidence = 1.78623e-05 | |
| I0407 15:32:58.470932 1004 sgd_solver.cpp:106] Iteration 14000, lr = 0.000972 | |
| I0407 15:33:36.353240 1004 solver.cpp:229] Iteration 14500, loss = 1.08598 | |
| I0407 15:33:36.353338 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 15:33:36.353356 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:33:36.353370 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 15:33:36.353384 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 15:33:36.353395 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 15:33:36.353407 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 15:33:36.353420 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 15:33:36.353431 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 15:33:36.353443 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:33:36.353456 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 15:33:36.353467 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:33:36.353479 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:33:36.353492 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:33:36.353502 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:33:36.353514 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:33:36.353526 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:33:36.353538 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:33:36.353549 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:33:36.353561 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:33:36.353574 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:33:36.353585 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:33:36.353596 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:33:36.353612 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.50985 (* 0.0454545 = 0.159538 loss) | |
| I0407 15:33:36.353626 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.73097 (* 0.0454545 = 0.16959 loss) | |
| I0407 15:33:36.353641 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.53435 (* 0.0454545 = 0.160652 loss) | |
| I0407 15:33:36.353654 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.80271 (* 0.0454545 = 0.17285 loss) | |
| I0407 15:33:36.353670 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.47641 (* 0.0454545 = 0.158019 loss) | |
| I0407 15:33:36.353684 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.73994 (* 0.0454545 = 0.124543 loss) | |
| I0407 15:33:36.353698 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.38175 (* 0.0454545 = 0.062807 loss) | |
| I0407 15:33:36.353711 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.384979 (* 0.0454545 = 0.0174991 loss) | |
| I0407 15:33:36.353725 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.372984 (* 0.0454545 = 0.0169538 loss) | |
| I0407 15:33:36.353739 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.400717 (* 0.0454545 = 0.0182144 loss) | |
| I0407 15:33:36.353754 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000189159 (* 0.0454545 = 8.59816e-06 loss) | |
| I0407 15:33:36.353768 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000180433 (* 0.0454545 = 8.20149e-06 loss) | |
| I0407 15:33:36.353782 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000180726 (* 0.0454545 = 8.21483e-06 loss) | |
| I0407 15:33:36.353796 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000185138 (* 0.0454545 = 8.41537e-06 loss) | |
| I0407 15:33:36.353811 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.00018514 (* 0.0454545 = 8.41543e-06 loss) | |
| I0407 15:33:36.353826 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000192635 (* 0.0454545 = 8.75612e-06 loss) | |
| I0407 15:33:36.353839 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000191507 (* 0.0454545 = 8.70488e-06 loss) | |
| I0407 15:33:36.353870 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000183933 (* 0.0454545 = 8.36057e-06 loss) | |
| I0407 15:33:36.353886 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000183102 (* 0.0454545 = 8.32284e-06 loss) | |
| I0407 15:33:36.353900 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000183928 (* 0.0454545 = 8.36036e-06 loss) | |
| I0407 15:33:36.353915 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000173287 (* 0.0454545 = 7.87667e-06 loss) | |
| I0407 15:33:36.353929 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00018814 (* 0.0454545 = 8.5518e-06 loss) | |
| I0407 15:33:36.353941 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:33:36.353953 1004 solver.cpp:245] Train net output #45: total_confidence = 1.86293e-06 | |
| I0407 15:33:36.353965 1004 sgd_solver.cpp:106] Iteration 14500, lr = 0.000971 | |
| I0407 15:34:14.105677 1004 solver.cpp:338] Iteration 15000, Testing net (#0) | |
| I0407 15:34:22.024494 1004 solver.cpp:393] Test loss: 0.992694 | |
| I0407 15:34:22.024539 1004 solver.cpp:406] Test net output #0: loss/accuracy01 = 0.004 | |
| I0407 15:34:22.024554 1004 solver.cpp:406] Test net output #1: loss/accuracy02 = 0.124 | |
| I0407 15:34:22.024567 1004 solver.cpp:406] Test net output #2: loss/accuracy03 = 0.091 | |
| I0407 15:34:22.024580 1004 solver.cpp:406] Test net output #3: loss/accuracy04 = 0.09 | |
| I0407 15:34:22.024590 1004 solver.cpp:406] Test net output #4: loss/accuracy05 = 0.212 | |
| I0407 15:34:22.024602 1004 solver.cpp:406] Test net output #5: loss/accuracy06 = 0.501 | |
| I0407 15:34:22.024613 1004 solver.cpp:406] Test net output #6: loss/accuracy07 = 0.894 | |
| I0407 15:34:22.024626 1004 solver.cpp:406] Test net output #7: loss/accuracy08 = 0.97 | |
| I0407 15:34:22.024636 1004 solver.cpp:406] Test net output #8: loss/accuracy09 = 0.995 | |
| I0407 15:34:22.024648 1004 solver.cpp:406] Test net output #9: loss/accuracy10 = 0.998 | |
| I0407 15:34:22.024659 1004 solver.cpp:406] Test net output #10: loss/accuracy11 = 1 | |
| I0407 15:34:22.024670 1004 solver.cpp:406] Test net output #11: loss/accuracy12 = 1 | |
| I0407 15:34:22.024682 1004 solver.cpp:406] Test net output #12: loss/accuracy13 = 1 | |
| I0407 15:34:22.024693 1004 solver.cpp:406] Test net output #13: loss/accuracy14 = 1 | |
| I0407 15:34:22.024704 1004 solver.cpp:406] Test net output #14: loss/accuracy15 = 1 | |
| I0407 15:34:22.024715 1004 solver.cpp:406] Test net output #15: loss/accuracy16 = 1 | |
| I0407 15:34:22.024725 1004 solver.cpp:406] Test net output #16: loss/accuracy17 = 1 | |
| I0407 15:34:22.024737 1004 solver.cpp:406] Test net output #17: loss/accuracy18 = 1 | |
| I0407 15:34:22.024749 1004 solver.cpp:406] Test net output #18: loss/accuracy19 = 1 | |
| I0407 15:34:22.024760 1004 solver.cpp:406] Test net output #19: loss/accuracy20 = 1 | |
| I0407 15:34:22.024770 1004 solver.cpp:406] Test net output #20: loss/accuracy21 = 1 | |
| I0407 15:34:22.024780 1004 solver.cpp:406] Test net output #21: loss/accuracy22 = 1 | |
| I0407 15:34:22.024796 1004 solver.cpp:406] Test net output #22: loss/loss01 = 3.39904 (* 0.0454545 = 0.154502 loss) | |
| I0407 15:34:22.024809 1004 solver.cpp:406] Test net output #23: loss/loss02 = 3.54274 (* 0.0454545 = 0.161034 loss) | |
| I0407 15:34:22.024823 1004 solver.cpp:406] Test net output #24: loss/loss03 = 3.65737 (* 0.0454545 = 0.166244 loss) | |
| I0407 15:34:22.024837 1004 solver.cpp:406] Test net output #25: loss/loss04 = 3.62152 (* 0.0454545 = 0.164615 loss) | |
| I0407 15:34:22.024850 1004 solver.cpp:406] Test net output #26: loss/loss05 = 3.51317 (* 0.0454545 = 0.15969 loss) | |
| I0407 15:34:22.024863 1004 solver.cpp:406] Test net output #27: loss/loss06 = 2.53455 (* 0.0454545 = 0.115207 loss) | |
| I0407 15:34:22.024876 1004 solver.cpp:406] Test net output #28: loss/loss07 = 1.00764 (* 0.0454545 = 0.0458019 loss) | |
| I0407 15:34:22.024889 1004 solver.cpp:406] Test net output #29: loss/loss08 = 0.360382 (* 0.0454545 = 0.016381 loss) | |
| I0407 15:34:22.024904 1004 solver.cpp:406] Test net output #30: loss/loss09 = 0.107153 (* 0.0454545 = 0.0048706 loss) | |
| I0407 15:34:22.024919 1004 solver.cpp:406] Test net output #31: loss/loss10 = 0.052984 (* 0.0454545 = 0.00240836 loss) | |
| I0407 15:34:22.024935 1004 solver.cpp:406] Test net output #32: loss/loss11 = 0.00358202 (* 0.0454545 = 0.000162819 loss) | |
| I0407 15:34:22.024948 1004 solver.cpp:406] Test net output #33: loss/loss12 = 0.00353524 (* 0.0454545 = 0.000160693 loss) | |
| I0407 15:34:22.024962 1004 solver.cpp:406] Test net output #34: loss/loss13 = 0.00353932 (* 0.0454545 = 0.000160878 loss) | |
| I0407 15:34:22.024976 1004 solver.cpp:406] Test net output #35: loss/loss14 = 0.00355675 (* 0.0454545 = 0.000161671 loss) | |
| I0407 15:34:22.024989 1004 solver.cpp:406] Test net output #36: loss/loss15 = 0.00357787 (* 0.0454545 = 0.00016263 loss) | |
| I0407 15:34:22.025003 1004 solver.cpp:406] Test net output #37: loss/loss16 = 0.00357851 (* 0.0454545 = 0.000162659 loss) | |
| I0407 15:34:22.025017 1004 solver.cpp:406] Test net output #38: loss/loss17 = 0.00355546 (* 0.0454545 = 0.000161612 loss) | |
| I0407 15:34:22.025065 1004 solver.cpp:406] Test net output #39: loss/loss18 = 0.00356064 (* 0.0454545 = 0.000161847 loss) | |
| I0407 15:34:22.025080 1004 solver.cpp:406] Test net output #40: loss/loss19 = 0.00356737 (* 0.0454545 = 0.000162153 loss) | |
| I0407 15:34:22.025094 1004 solver.cpp:406] Test net output #41: loss/loss20 = 0.00355631 (* 0.0454545 = 0.00016165 loss) | |
| I0407 15:34:22.025109 1004 solver.cpp:406] Test net output #42: loss/loss21 = 0.00357018 (* 0.0454545 = 0.000162281 loss) | |
| I0407 15:34:22.025121 1004 solver.cpp:406] Test net output #43: loss/loss22 = 0.00354827 (* 0.0454545 = 0.000161285 loss) | |
| I0407 15:34:22.025133 1004 solver.cpp:406] Test net output #44: total_accuracy = 0 | |
| I0407 15:34:22.025146 1004 solver.cpp:406] Test net output #45: total_confidence = 2.68311e-06 | |
| I0407 15:34:22.047554 1004 solver.cpp:229] Iteration 15000, loss = 1.08425 | |
| I0407 15:34:22.047582 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:34:22.047597 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:34:22.047610 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 15:34:22.047621 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 15:34:22.047633 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 15:34:22.047644 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 15:34:22.047657 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.625 | |
| I0407 15:34:22.047667 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 15:34:22.047679 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:34:22.047694 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:34:22.047708 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:34:22.047719 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:34:22.047730 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:34:22.047741 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:34:22.047754 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:34:22.047765 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:34:22.047776 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:34:22.047787 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:34:22.047799 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:34:22.047811 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:34:22.047821 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:34:22.047833 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:34:22.047847 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.87604 (* 0.0454545 = 0.176184 loss) | |
| I0407 15:34:22.047862 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.81071 (* 0.0454545 = 0.173214 loss) | |
| I0407 15:34:22.047875 1004 solver.cpp:245] Train net output #24: loss/loss03 = 4.06766 (* 0.0454545 = 0.184894 loss) | |
| I0407 15:34:22.047888 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.89003 (* 0.0454545 = 0.17682 loss) | |
| I0407 15:34:22.047902 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.52966 (* 0.0454545 = 0.160439 loss) | |
| I0407 15:34:22.047915 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.522 (* 0.0454545 = 0.114636 loss) | |
| I0407 15:34:22.047930 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.94924 (* 0.0454545 = 0.0886019 loss) | |
| I0407 15:34:22.047942 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.406369 (* 0.0454545 = 0.0184713 loss) | |
| I0407 15:34:22.047956 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.429681 (* 0.0454545 = 0.019531 loss) | |
| I0407 15:34:22.047971 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0183738 (* 0.0454545 = 0.000835174 loss) | |
| I0407 15:34:22.048002 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000468383 (* 0.0454545 = 2.12902e-05 loss) | |
| I0407 15:34:22.048017 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000459442 (* 0.0454545 = 2.08837e-05 loss) | |
| I0407 15:34:22.048032 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000461319 (* 0.0454545 = 2.0969e-05 loss) | |
| I0407 15:34:22.048045 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000450346 (* 0.0454545 = 2.04703e-05 loss) | |
| I0407 15:34:22.048059 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000454445 (* 0.0454545 = 2.06566e-05 loss) | |
| I0407 15:34:22.048076 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000453403 (* 0.0454545 = 2.06092e-05 loss) | |
| I0407 15:34:22.048090 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000449861 (* 0.0454545 = 2.04482e-05 loss) | |
| I0407 15:34:22.048105 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000451919 (* 0.0454545 = 2.05418e-05 loss) | |
| I0407 15:34:22.048118 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000460572 (* 0.0454545 = 2.09351e-05 loss) | |
| I0407 15:34:22.048132 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000465239 (* 0.0454545 = 2.11472e-05 loss) | |
| I0407 15:34:22.048146 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000443347 (* 0.0454545 = 2.01521e-05 loss) | |
| I0407 15:34:22.048161 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000427002 (* 0.0454545 = 1.94092e-05 loss) | |
| I0407 15:34:22.048172 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:34:22.048183 1004 solver.cpp:245] Train net output #45: total_confidence = 2.6298e-05 | |
| I0407 15:34:22.048198 1004 sgd_solver.cpp:106] Iteration 15000, lr = 0.00097 | |
| I0407 15:34:59.622711 1004 solver.cpp:229] Iteration 15500, loss = 1.08939 | |
| I0407 15:34:59.622900 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:34:59.622921 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:34:59.622934 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 15:34:59.622947 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 15:34:59.622959 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.0625 | |
| I0407 15:34:59.622972 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 15:34:59.622983 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 15:34:59.622995 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 15:34:59.623008 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:34:59.623019 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 15:34:59.623030 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:34:59.623042 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:34:59.623054 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:34:59.623065 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:34:59.623077 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:34:59.623088 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:34:59.623100 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:34:59.623111 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:34:59.623124 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:34:59.623136 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:34:59.623147 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:34:59.623159 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:34:59.623174 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.78074 (* 0.0454545 = 0.171852 loss) | |
| I0407 15:34:59.623188 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.76763 (* 0.0454545 = 0.171256 loss) | |
| I0407 15:34:59.623203 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.88491 (* 0.0454545 = 0.176587 loss) | |
| I0407 15:34:59.623216 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.90229 (* 0.0454545 = 0.177377 loss) | |
| I0407 15:34:59.623230 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.85611 (* 0.0454545 = 0.175278 loss) | |
| I0407 15:34:59.623245 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.01755 (* 0.0454545 = 0.137161 loss) | |
| I0407 15:34:59.623257 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.60777 (* 0.0454545 = 0.0730804 loss) | |
| I0407 15:34:59.623271 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.899085 (* 0.0454545 = 0.0408675 loss) | |
| I0407 15:34:59.623286 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.416061 (* 0.0454545 = 0.0189118 loss) | |
| I0407 15:34:59.623299 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.528219 (* 0.0454545 = 0.0240099 loss) | |
| I0407 15:34:59.623313 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000716398 (* 0.0454545 = 3.25636e-05 loss) | |
| I0407 15:34:59.623348 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000687722 (* 0.0454545 = 3.12601e-05 loss) | |
| I0407 15:34:59.623363 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000713235 (* 0.0454545 = 3.24198e-05 loss) | |
| I0407 15:34:59.623378 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000700056 (* 0.0454545 = 3.18207e-05 loss) | |
| I0407 15:34:59.623392 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000730427 (* 0.0454545 = 3.32012e-05 loss) | |
| I0407 15:34:59.623406 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000698136 (* 0.0454545 = 3.17335e-05 loss) | |
| I0407 15:34:59.623420 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000729347 (* 0.0454545 = 3.31522e-05 loss) | |
| I0407 15:34:59.623450 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000737804 (* 0.0454545 = 3.35366e-05 loss) | |
| I0407 15:34:59.623464 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000701054 (* 0.0454545 = 3.18661e-05 loss) | |
| I0407 15:34:59.623479 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000728026 (* 0.0454545 = 3.30921e-05 loss) | |
| I0407 15:34:59.623493 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000713765 (* 0.0454545 = 3.24439e-05 loss) | |
| I0407 15:34:59.623507 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000718554 (* 0.0454545 = 3.26616e-05 loss) | |
| I0407 15:34:59.623519 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:34:59.623531 1004 solver.cpp:245] Train net output #45: total_confidence = 1.02379e-05 | |
| I0407 15:34:59.623544 1004 sgd_solver.cpp:106] Iteration 15500, lr = 0.000969 | |
| I0407 15:35:37.432926 1004 solver.cpp:229] Iteration 16000, loss = 1.09374 | |
| I0407 15:35:37.433045 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:35:37.433066 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:35:37.433079 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 15:35:37.433092 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 15:35:37.433104 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 15:35:37.433116 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 15:35:37.433128 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.625 | |
| I0407 15:35:37.433140 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 15:35:37.433152 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:35:37.433163 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:35:37.433176 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:35:37.433187 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:35:37.433198 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:35:37.433210 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:35:37.433221 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:35:37.433233 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:35:37.433244 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:35:37.433256 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:35:37.433269 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:35:37.433279 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:35:37.433291 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:35:37.433302 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:35:37.433318 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.70857 (* 0.0454545 = 0.168572 loss) | |
| I0407 15:35:37.433333 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.56276 (* 0.0454545 = 0.161944 loss) | |
| I0407 15:35:37.433347 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.94607 (* 0.0454545 = 0.179367 loss) | |
| I0407 15:35:37.433360 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.90615 (* 0.0454545 = 0.177552 loss) | |
| I0407 15:35:37.433374 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.37735 (* 0.0454545 = 0.153516 loss) | |
| I0407 15:35:37.433387 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.7141 (* 0.0454545 = 0.123368 loss) | |
| I0407 15:35:37.433401 1004 solver.cpp:245] Train net output #28: loss/loss07 = 2.08184 (* 0.0454545 = 0.0946292 loss) | |
| I0407 15:35:37.433415 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.09797 (* 0.0454545 = 0.0499076 loss) | |
| I0407 15:35:37.433431 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0561588 (* 0.0454545 = 0.00255267 loss) | |
| I0407 15:35:37.433445 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0205622 (* 0.0454545 = 0.000934643 loss) | |
| I0407 15:35:37.433459 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000595901 (* 0.0454545 = 2.70864e-05 loss) | |
| I0407 15:35:37.433473 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000570202 (* 0.0454545 = 2.59183e-05 loss) | |
| I0407 15:35:37.433487 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000597522 (* 0.0454545 = 2.71601e-05 loss) | |
| I0407 15:35:37.433501 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000607181 (* 0.0454545 = 2.75991e-05 loss) | |
| I0407 15:35:37.433516 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000601167 (* 0.0454545 = 2.73258e-05 loss) | |
| I0407 15:35:37.433529 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000571918 (* 0.0454545 = 2.59963e-05 loss) | |
| I0407 15:35:37.433543 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000585181 (* 0.0454545 = 2.65992e-05 loss) | |
| I0407 15:35:37.433575 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000610734 (* 0.0454545 = 2.77606e-05 loss) | |
| I0407 15:35:37.433590 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000611521 (* 0.0454545 = 2.77964e-05 loss) | |
| I0407 15:35:37.433604 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.00059102 (* 0.0454545 = 2.68646e-05 loss) | |
| I0407 15:35:37.433619 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00060173 (* 0.0454545 = 2.73514e-05 loss) | |
| I0407 15:35:37.433632 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000591761 (* 0.0454545 = 2.68982e-05 loss) | |
| I0407 15:35:37.433645 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:35:37.433656 1004 solver.cpp:245] Train net output #45: total_confidence = 1.67051e-06 | |
| I0407 15:35:37.433670 1004 sgd_solver.cpp:106] Iteration 16000, lr = 0.000968 | |
| I0407 15:36:15.820094 1004 solver.cpp:229] Iteration 16500, loss = 1.09274 | |
| I0407 15:36:15.820194 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 15:36:15.820212 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:36:15.820225 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 15:36:15.820240 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 15:36:15.820253 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 15:36:15.820266 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 15:36:15.820278 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.625 | |
| I0407 15:36:15.820289 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 15:36:15.820302 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:36:15.820313 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:36:15.820325 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:36:15.820338 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:36:15.820349 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:36:15.820360 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:36:15.820372 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:36:15.820384 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:36:15.820395 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:36:15.820406 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:36:15.820418 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:36:15.820430 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:36:15.820441 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:36:15.820453 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:36:15.820469 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.55986 (* 0.0454545 = 0.161812 loss) | |
| I0407 15:36:15.820484 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.70504 (* 0.0454545 = 0.168411 loss) | |
| I0407 15:36:15.820498 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.78317 (* 0.0454545 = 0.171962 loss) | |
| I0407 15:36:15.820513 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.87919 (* 0.0454545 = 0.176327 loss) | |
| I0407 15:36:15.820526 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.52194 (* 0.0454545 = 0.160088 loss) | |
| I0407 15:36:15.820540 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.78528 (* 0.0454545 = 0.126604 loss) | |
| I0407 15:36:15.820554 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.99827 (* 0.0454545 = 0.0908304 loss) | |
| I0407 15:36:15.820569 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.817571 (* 0.0454545 = 0.0371623 loss) | |
| I0407 15:36:15.820582 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.491203 (* 0.0454545 = 0.0223274 loss) | |
| I0407 15:36:15.820596 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0477316 (* 0.0454545 = 0.00216962 loss) | |
| I0407 15:36:15.820611 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.0015289 (* 0.0454545 = 6.94956e-05 loss) | |
| I0407 15:36:15.820626 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00145236 (* 0.0454545 = 6.60162e-05 loss) | |
| I0407 15:36:15.820641 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.0015774 (* 0.0454545 = 7.16998e-05 loss) | |
| I0407 15:36:15.820654 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00153851 (* 0.0454545 = 6.99323e-05 loss) | |
| I0407 15:36:15.820668 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.00150353 (* 0.0454545 = 6.83422e-05 loss) | |
| I0407 15:36:15.820683 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.0015191 (* 0.0454545 = 6.90498e-05 loss) | |
| I0407 15:36:15.820698 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.00149292 (* 0.0454545 = 6.78601e-05 loss) | |
| I0407 15:36:15.820729 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.00151446 (* 0.0454545 = 6.88393e-05 loss) | |
| I0407 15:36:15.820744 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00153899 (* 0.0454545 = 6.9954e-05 loss) | |
| I0407 15:36:15.820758 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.00154207 (* 0.0454545 = 7.00943e-05 loss) | |
| I0407 15:36:15.820772 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00148372 (* 0.0454545 = 6.74418e-05 loss) | |
| I0407 15:36:15.820786 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00151576 (* 0.0454545 = 6.88983e-05 loss) | |
| I0407 15:36:15.820798 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:36:15.820809 1004 solver.cpp:245] Train net output #45: total_confidence = 2.06633e-06 | |
| I0407 15:36:15.820822 1004 sgd_solver.cpp:106] Iteration 16500, lr = 0.000967 | |
| I0407 15:36:54.689404 1004 solver.cpp:229] Iteration 17000, loss = 1.08644 | |
| I0407 15:36:54.689512 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 15:36:54.689533 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:36:54.689546 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 15:36:54.689559 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 15:36:54.689571 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 15:36:54.689584 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 15:36:54.689595 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 15:36:54.689609 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 15:36:54.689620 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:36:54.689631 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:36:54.689643 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:36:54.689654 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:36:54.689666 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:36:54.689678 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:36:54.689689 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:36:54.689702 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:36:54.689713 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:36:54.689724 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:36:54.689735 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:36:54.689748 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:36:54.689759 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:36:54.689770 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:36:54.689786 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.79318 (* 0.0454545 = 0.172417 loss) | |
| I0407 15:36:54.689800 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.91659 (* 0.0454545 = 0.178027 loss) | |
| I0407 15:36:54.689815 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.94018 (* 0.0454545 = 0.179099 loss) | |
| I0407 15:36:54.689828 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.94847 (* 0.0454545 = 0.179476 loss) | |
| I0407 15:36:54.689842 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.6449 (* 0.0454545 = 0.165677 loss) | |
| I0407 15:36:54.689857 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.17989 (* 0.0454545 = 0.14454 loss) | |
| I0407 15:36:54.689870 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.73828 (* 0.0454545 = 0.0790128 loss) | |
| I0407 15:36:54.689884 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.723993 (* 0.0454545 = 0.0329088 loss) | |
| I0407 15:36:54.689898 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0447649 (* 0.0454545 = 0.00203477 loss) | |
| I0407 15:36:54.689913 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0206297 (* 0.0454545 = 0.000937714 loss) | |
| I0407 15:36:54.689930 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000394759 (* 0.0454545 = 1.79436e-05 loss) | |
| I0407 15:36:54.689945 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000390721 (* 0.0454545 = 1.776e-05 loss) | |
| I0407 15:36:54.689960 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000409754 (* 0.0454545 = 1.86252e-05 loss) | |
| I0407 15:36:54.689975 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000413262 (* 0.0454545 = 1.87847e-05 loss) | |
| I0407 15:36:54.689988 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.0004248 (* 0.0454545 = 1.93091e-05 loss) | |
| I0407 15:36:54.690002 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000394169 (* 0.0454545 = 1.79168e-05 loss) | |
| I0407 15:36:54.690016 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000391947 (* 0.0454545 = 1.78158e-05 loss) | |
| I0407 15:36:54.690047 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000416827 (* 0.0454545 = 1.89467e-05 loss) | |
| I0407 15:36:54.690062 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00040785 (* 0.0454545 = 1.85386e-05 loss) | |
| I0407 15:36:54.690076 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000405886 (* 0.0454545 = 1.84494e-05 loss) | |
| I0407 15:36:54.690090 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000422988 (* 0.0454545 = 1.92267e-05 loss) | |
| I0407 15:36:54.690105 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000406121 (* 0.0454545 = 1.846e-05 loss) | |
| I0407 15:36:54.690117 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:36:54.690129 1004 solver.cpp:245] Train net output #45: total_confidence = 2.91666e-05 | |
| I0407 15:36:54.690142 1004 sgd_solver.cpp:106] Iteration 17000, lr = 0.000966 | |
| I0407 15:37:33.037350 1004 solver.cpp:229] Iteration 17500, loss = 1.08365 | |
| I0407 15:37:33.037482 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:37:33.037502 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:37:33.037515 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 15:37:33.037528 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 15:37:33.037539 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 15:37:33.037551 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.1875 | |
| I0407 15:37:33.037564 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 15:37:33.037575 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 15:37:33.037587 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.8125 | |
| I0407 15:37:33.037600 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 15:37:33.037611 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:37:33.037622 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:37:33.037634 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:37:33.037645 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:37:33.037657 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:37:33.037669 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:37:33.037680 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:37:33.037691 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:37:33.037703 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:37:33.037714 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:37:33.037726 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:37:33.037737 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:37:33.037753 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.80508 (* 0.0454545 = 0.172958 loss) | |
| I0407 15:37:33.037768 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.7154 (* 0.0454545 = 0.168882 loss) | |
| I0407 15:37:33.037782 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.84135 (* 0.0454545 = 0.174607 loss) | |
| I0407 15:37:33.037796 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.85287 (* 0.0454545 = 0.17513 loss) | |
| I0407 15:37:33.037811 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.58895 (* 0.0454545 = 0.163134 loss) | |
| I0407 15:37:33.037823 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.7299 (* 0.0454545 = 0.169541 loss) | |
| I0407 15:37:33.037837 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.71479 (* 0.0454545 = 0.0779449 loss) | |
| I0407 15:37:33.037852 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.09131 (* 0.0454545 = 0.0496051 loss) | |
| I0407 15:37:33.037865 1004 solver.cpp:245] Train net output #30: loss/loss09 = 1.19238 (* 0.0454545 = 0.0541993 loss) | |
| I0407 15:37:33.037879 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.409212 (* 0.0454545 = 0.0186005 loss) | |
| I0407 15:37:33.037894 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000633054 (* 0.0454545 = 2.87752e-05 loss) | |
| I0407 15:37:33.037909 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000639348 (* 0.0454545 = 2.90613e-05 loss) | |
| I0407 15:37:33.037926 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000609616 (* 0.0454545 = 2.77098e-05 loss) | |
| I0407 15:37:33.037940 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00061596 (* 0.0454545 = 2.79982e-05 loss) | |
| I0407 15:37:33.037955 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000610567 (* 0.0454545 = 2.7753e-05 loss) | |
| I0407 15:37:33.037969 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000623147 (* 0.0454545 = 2.83248e-05 loss) | |
| I0407 15:37:33.037983 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000649452 (* 0.0454545 = 2.95205e-05 loss) | |
| I0407 15:37:33.038012 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000633214 (* 0.0454545 = 2.87825e-05 loss) | |
| I0407 15:37:33.038027 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000642867 (* 0.0454545 = 2.92212e-05 loss) | |
| I0407 15:37:33.038040 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000593523 (* 0.0454545 = 2.69783e-05 loss) | |
| I0407 15:37:33.038054 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000646974 (* 0.0454545 = 2.94079e-05 loss) | |
| I0407 15:37:33.038069 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000624764 (* 0.0454545 = 2.83984e-05 loss) | |
| I0407 15:37:33.038080 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:37:33.038092 1004 solver.cpp:245] Train net output #45: total_confidence = 2.48492e-06 | |
| I0407 15:37:33.038105 1004 sgd_solver.cpp:106] Iteration 17500, lr = 0.000965 | |
| I0407 15:38:11.956302 1004 solver.cpp:229] Iteration 18000, loss = 1.07854 | |
| I0407 15:38:11.956413 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:38:11.956431 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:38:11.956444 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 15:38:11.956456 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 15:38:11.956468 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 15:38:11.956480 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.25 | |
| I0407 15:38:11.956492 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.5 | |
| I0407 15:38:11.956504 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 15:38:11.956516 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:38:11.956527 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:38:11.956539 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:38:11.956550 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:38:11.956562 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:38:11.956574 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:38:11.956585 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:38:11.956596 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:38:11.956609 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:38:11.956619 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:38:11.956631 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:38:11.956642 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:38:11.956655 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:38:11.956665 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:38:11.956681 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.35982 (* 0.0454545 = 0.152719 loss) | |
| I0407 15:38:11.956696 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.53419 (* 0.0454545 = 0.160645 loss) | |
| I0407 15:38:11.956709 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.59371 (* 0.0454545 = 0.163351 loss) | |
| I0407 15:38:11.956723 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.50852 (* 0.0454545 = 0.159478 loss) | |
| I0407 15:38:11.956737 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.18566 (* 0.0454545 = 0.144803 loss) | |
| I0407 15:38:11.956750 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.25175 (* 0.0454545 = 0.147807 loss) | |
| I0407 15:38:11.956764 1004 solver.cpp:245] Train net output #28: loss/loss07 = 2.35856 (* 0.0454545 = 0.107207 loss) | |
| I0407 15:38:11.956779 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.06985 (* 0.0454545 = 0.0486296 loss) | |
| I0407 15:38:11.956792 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.401095 (* 0.0454545 = 0.0182316 loss) | |
| I0407 15:38:11.956806 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0277029 (* 0.0454545 = 0.00125922 loss) | |
| I0407 15:38:11.956820 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000607471 (* 0.0454545 = 2.76123e-05 loss) | |
| I0407 15:38:11.956835 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000611291 (* 0.0454545 = 2.77859e-05 loss) | |
| I0407 15:38:11.956850 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000627329 (* 0.0454545 = 2.85149e-05 loss) | |
| I0407 15:38:11.956863 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000579516 (* 0.0454545 = 2.63416e-05 loss) | |
| I0407 15:38:11.956877 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000614811 (* 0.0454545 = 2.7946e-05 loss) | |
| I0407 15:38:11.956892 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000566081 (* 0.0454545 = 2.5731e-05 loss) | |
| I0407 15:38:11.956905 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000582016 (* 0.0454545 = 2.64553e-05 loss) | |
| I0407 15:38:11.956939 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000616682 (* 0.0454545 = 2.8031e-05 loss) | |
| I0407 15:38:11.956954 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000579724 (* 0.0454545 = 2.63511e-05 loss) | |
| I0407 15:38:11.956969 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000595979 (* 0.0454545 = 2.70899e-05 loss) | |
| I0407 15:38:11.956982 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000586387 (* 0.0454545 = 2.6654e-05 loss) | |
| I0407 15:38:11.956996 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000594903 (* 0.0454545 = 2.7041e-05 loss) | |
| I0407 15:38:11.957008 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:38:11.957020 1004 solver.cpp:245] Train net output #45: total_confidence = 8.26735e-06 | |
| I0407 15:38:11.957033 1004 sgd_solver.cpp:106] Iteration 18000, lr = 0.000964 | |
| I0407 15:38:51.017987 1004 solver.cpp:229] Iteration 18500, loss = 1.08661 | |
| I0407 15:38:51.018097 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:38:51.018116 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:38:51.018129 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 15:38:51.018142 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 15:38:51.018154 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 15:38:51.018167 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 15:38:51.018178 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 15:38:51.018190 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 15:38:51.018203 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:38:51.018214 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:38:51.018226 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:38:51.018237 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:38:51.018249 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:38:51.018261 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:38:51.018272 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:38:51.018285 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:38:51.018296 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:38:51.018307 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:38:51.018319 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:38:51.018331 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:38:51.018342 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:38:51.018353 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:38:51.018368 1004 solver.cpp:245] Train net output #22: loss/loss01 = 4.00116 (* 0.0454545 = 0.181871 loss) | |
| I0407 15:38:51.018383 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.89501 (* 0.0454545 = 0.177046 loss) | |
| I0407 15:38:51.018396 1004 solver.cpp:245] Train net output #24: loss/loss03 = 4.08875 (* 0.0454545 = 0.185852 loss) | |
| I0407 15:38:51.018410 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.8507 (* 0.0454545 = 0.175032 loss) | |
| I0407 15:38:51.018425 1004 solver.cpp:245] Train net output #26: loss/loss05 = 4.07659 (* 0.0454545 = 0.185299 loss) | |
| I0407 15:38:51.018440 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.08872 (* 0.0454545 = 0.140396 loss) | |
| I0407 15:38:51.018453 1004 solver.cpp:245] Train net output #28: loss/loss07 = 2.00602 (* 0.0454545 = 0.0911829 loss) | |
| I0407 15:38:51.018467 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.610857 (* 0.0454545 = 0.0277663 loss) | |
| I0407 15:38:51.018481 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.070365 (* 0.0454545 = 0.00319841 loss) | |
| I0407 15:38:51.018496 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0294157 (* 0.0454545 = 0.00133708 loss) | |
| I0407 15:38:51.018510 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000902399 (* 0.0454545 = 4.10182e-05 loss) | |
| I0407 15:38:51.018524 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000920532 (* 0.0454545 = 4.18423e-05 loss) | |
| I0407 15:38:51.018538 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000884216 (* 0.0454545 = 4.01917e-05 loss) | |
| I0407 15:38:51.018553 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000923359 (* 0.0454545 = 4.19709e-05 loss) | |
| I0407 15:38:51.018566 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000865518 (* 0.0454545 = 3.93417e-05 loss) | |
| I0407 15:38:51.018580 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000912268 (* 0.0454545 = 4.14667e-05 loss) | |
| I0407 15:38:51.018594 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000824609 (* 0.0454545 = 3.74822e-05 loss) | |
| I0407 15:38:51.018625 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000875479 (* 0.0454545 = 3.97945e-05 loss) | |
| I0407 15:38:51.018640 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000865417 (* 0.0454545 = 3.93372e-05 loss) | |
| I0407 15:38:51.018654 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000814129 (* 0.0454545 = 3.70059e-05 loss) | |
| I0407 15:38:51.018668 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000846429 (* 0.0454545 = 3.84741e-05 loss) | |
| I0407 15:38:51.018682 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000817837 (* 0.0454545 = 3.71744e-05 loss) | |
| I0407 15:38:51.018693 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:38:51.018705 1004 solver.cpp:245] Train net output #45: total_confidence = 3.09178e-06 | |
| I0407 15:38:51.018718 1004 sgd_solver.cpp:106] Iteration 18500, lr = 0.000963 | |
| I0407 15:39:29.169054 1004 solver.cpp:229] Iteration 19000, loss = 1.08647 | |
| I0407 15:39:29.169162 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.1875 | |
| I0407 15:39:29.169179 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.125 | |
| I0407 15:39:29.169191 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:39:29.169204 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 15:39:29.169215 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 15:39:29.169229 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 15:39:29.169240 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 15:39:29.169252 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 15:39:29.169263 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:39:29.169275 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:39:29.169286 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:39:29.169298 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:39:29.169311 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:39:29.169322 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:39:29.169333 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:39:29.169344 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:39:29.169356 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:39:29.169368 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:39:29.169379 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:39:29.169391 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:39:29.169402 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:39:29.169414 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:39:29.169430 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.70272 (* 0.0454545 = 0.168305 loss) | |
| I0407 15:39:29.169445 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.60447 (* 0.0454545 = 0.16384 loss) | |
| I0407 15:39:29.169458 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.92786 (* 0.0454545 = 0.178539 loss) | |
| I0407 15:39:29.169472 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.72508 (* 0.0454545 = 0.169322 loss) | |
| I0407 15:39:29.169486 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.19015 (* 0.0454545 = 0.145007 loss) | |
| I0407 15:39:29.169500 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.59097 (* 0.0454545 = 0.117771 loss) | |
| I0407 15:39:29.169513 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.15914 (* 0.0454545 = 0.0526883 loss) | |
| I0407 15:39:29.169528 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.751197 (* 0.0454545 = 0.0341453 loss) | |
| I0407 15:39:29.169541 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0431115 (* 0.0454545 = 0.00195961 loss) | |
| I0407 15:39:29.169555 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0196091 (* 0.0454545 = 0.000891324 loss) | |
| I0407 15:39:29.169570 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000461002 (* 0.0454545 = 2.09546e-05 loss) | |
| I0407 15:39:29.169584 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000433258 (* 0.0454545 = 1.96935e-05 loss) | |
| I0407 15:39:29.169600 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000452481 (* 0.0454545 = 2.05673e-05 loss) | |
| I0407 15:39:29.169613 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000462287 (* 0.0454545 = 2.10131e-05 loss) | |
| I0407 15:39:29.169627 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000484398 (* 0.0454545 = 2.20181e-05 loss) | |
| I0407 15:39:29.169641 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000481924 (* 0.0454545 = 2.19056e-05 loss) | |
| I0407 15:39:29.169656 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000441422 (* 0.0454545 = 2.00646e-05 loss) | |
| I0407 15:39:29.169685 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000493968 (* 0.0454545 = 2.24531e-05 loss) | |
| I0407 15:39:29.169700 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000439087 (* 0.0454545 = 1.99585e-05 loss) | |
| I0407 15:39:29.169715 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000435356 (* 0.0454545 = 1.97889e-05 loss) | |
| I0407 15:39:29.169729 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000481684 (* 0.0454545 = 2.18947e-05 loss) | |
| I0407 15:39:29.169742 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000477002 (* 0.0454545 = 2.16819e-05 loss) | |
| I0407 15:39:29.169754 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:39:29.169766 1004 solver.cpp:245] Train net output #45: total_confidence = 5.1267e-06 | |
| I0407 15:39:29.169780 1004 sgd_solver.cpp:106] Iteration 19000, lr = 0.000962 | |
| I0407 15:40:07.537747 1004 solver.cpp:229] Iteration 19500, loss = 1.08625 | |
| I0407 15:40:07.537879 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 15:40:07.537897 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:40:07.537911 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 15:40:07.537926 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 15:40:07.537940 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 15:40:07.537952 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 15:40:07.537964 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.875 | |
| I0407 15:40:07.537976 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 15:40:07.537988 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:40:07.538000 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:40:07.538012 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:40:07.538023 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:40:07.538034 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:40:07.538045 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:40:07.538058 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:40:07.538069 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:40:07.538080 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:40:07.538092 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:40:07.538105 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:40:07.538116 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:40:07.538127 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:40:07.538139 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:40:07.538154 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.67847 (* 0.0454545 = 0.167203 loss) | |
| I0407 15:40:07.538169 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.94385 (* 0.0454545 = 0.179266 loss) | |
| I0407 15:40:07.538182 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.59042 (* 0.0454545 = 0.163201 loss) | |
| I0407 15:40:07.538197 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.61463 (* 0.0454545 = 0.164301 loss) | |
| I0407 15:40:07.538210 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.24978 (* 0.0454545 = 0.147718 loss) | |
| I0407 15:40:07.538224 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.94551 (* 0.0454545 = 0.133887 loss) | |
| I0407 15:40:07.538238 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.936715 (* 0.0454545 = 0.0425779 loss) | |
| I0407 15:40:07.538252 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.102169 (* 0.0454545 = 0.00464404 loss) | |
| I0407 15:40:07.538267 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0329142 (* 0.0454545 = 0.0014961 loss) | |
| I0407 15:40:07.538281 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0130219 (* 0.0454545 = 0.000591905 loss) | |
| I0407 15:40:07.538296 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000225793 (* 0.0454545 = 1.02633e-05 loss) | |
| I0407 15:40:07.538311 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000223837 (* 0.0454545 = 1.01744e-05 loss) | |
| I0407 15:40:07.538324 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000240221 (* 0.0454545 = 1.09191e-05 loss) | |
| I0407 15:40:07.538338 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000240478 (* 0.0454545 = 1.09308e-05 loss) | |
| I0407 15:40:07.538353 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000241848 (* 0.0454545 = 1.09931e-05 loss) | |
| I0407 15:40:07.538367 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000247471 (* 0.0454545 = 1.12487e-05 loss) | |
| I0407 15:40:07.538381 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000235313 (* 0.0454545 = 1.06961e-05 loss) | |
| I0407 15:40:07.538408 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000226373 (* 0.0454545 = 1.02897e-05 loss) | |
| I0407 15:40:07.538424 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000231751 (* 0.0454545 = 1.05341e-05 loss) | |
| I0407 15:40:07.538437 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000235625 (* 0.0454545 = 1.07102e-05 loss) | |
| I0407 15:40:07.538452 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000247534 (* 0.0454545 = 1.12515e-05 loss) | |
| I0407 15:40:07.538466 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000243962 (* 0.0454545 = 1.10892e-05 loss) | |
| I0407 15:40:07.538478 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:40:07.538489 1004 solver.cpp:245] Train net output #45: total_confidence = 2.28272e-05 | |
| I0407 15:40:07.538503 1004 sgd_solver.cpp:106] Iteration 19500, lr = 0.000961 | |
| I0407 15:40:46.403219 1004 solver.cpp:338] Iteration 20000, Testing net (#0) | |
| I0407 15:40:54.327031 1004 solver.cpp:393] Test loss: 0.962223 | |
| I0407 15:40:54.327076 1004 solver.cpp:406] Test net output #0: loss/accuracy01 = 0.02 | |
| I0407 15:40:54.327093 1004 solver.cpp:406] Test net output #1: loss/accuracy02 = 0.124 | |
| I0407 15:40:54.327106 1004 solver.cpp:406] Test net output #2: loss/accuracy03 = 0.077 | |
| I0407 15:40:54.327118 1004 solver.cpp:406] Test net output #3: loss/accuracy04 = 0.091 | |
| I0407 15:40:54.327131 1004 solver.cpp:406] Test net output #4: loss/accuracy05 = 0.213 | |
| I0407 15:40:54.327142 1004 solver.cpp:406] Test net output #5: loss/accuracy06 = 0.502 | |
| I0407 15:40:54.327153 1004 solver.cpp:406] Test net output #6: loss/accuracy07 = 0.894 | |
| I0407 15:40:54.327165 1004 solver.cpp:406] Test net output #7: loss/accuracy08 = 0.97 | |
| I0407 15:40:54.327177 1004 solver.cpp:406] Test net output #8: loss/accuracy09 = 0.995 | |
| I0407 15:40:54.327188 1004 solver.cpp:406] Test net output #9: loss/accuracy10 = 0.998 | |
| I0407 15:40:54.327199 1004 solver.cpp:406] Test net output #10: loss/accuracy11 = 1 | |
| I0407 15:40:54.327210 1004 solver.cpp:406] Test net output #11: loss/accuracy12 = 1 | |
| I0407 15:40:54.327221 1004 solver.cpp:406] Test net output #12: loss/accuracy13 = 1 | |
| I0407 15:40:54.327232 1004 solver.cpp:406] Test net output #13: loss/accuracy14 = 1 | |
| I0407 15:40:54.327244 1004 solver.cpp:406] Test net output #14: loss/accuracy15 = 1 | |
| I0407 15:40:54.327255 1004 solver.cpp:406] Test net output #15: loss/accuracy16 = 1 | |
| I0407 15:40:54.327265 1004 solver.cpp:406] Test net output #16: loss/accuracy17 = 1 | |
| I0407 15:40:54.327277 1004 solver.cpp:406] Test net output #17: loss/accuracy18 = 1 | |
| I0407 15:40:54.327288 1004 solver.cpp:406] Test net output #18: loss/accuracy19 = 1 | |
| I0407 15:40:54.327299 1004 solver.cpp:406] Test net output #19: loss/accuracy20 = 1 | |
| I0407 15:40:54.327311 1004 solver.cpp:406] Test net output #20: loss/accuracy21 = 1 | |
| I0407 15:40:54.327342 1004 solver.cpp:406] Test net output #21: loss/accuracy22 = 1 | |
| I0407 15:40:54.327359 1004 solver.cpp:406] Test net output #22: loss/loss01 = 3.29439 (* 0.0454545 = 0.149745 loss) | |
| I0407 15:40:54.327373 1004 solver.cpp:406] Test net output #23: loss/loss02 = 3.49848 (* 0.0454545 = 0.159022 loss) | |
| I0407 15:40:54.327388 1004 solver.cpp:406] Test net output #24: loss/loss03 = 3.59194 (* 0.0454545 = 0.16327 loss) | |
| I0407 15:40:54.327401 1004 solver.cpp:406] Test net output #25: loss/loss04 = 3.53872 (* 0.0454545 = 0.160851 loss) | |
| I0407 15:40:54.327414 1004 solver.cpp:406] Test net output #26: loss/loss05 = 3.44184 (* 0.0454545 = 0.156447 loss) | |
| I0407 15:40:54.327428 1004 solver.cpp:406] Test net output #27: loss/loss06 = 2.45932 (* 0.0454545 = 0.111787 loss) | |
| I0407 15:40:54.327441 1004 solver.cpp:406] Test net output #28: loss/loss07 = 0.871082 (* 0.0454545 = 0.0395946 loss) | |
| I0407 15:40:54.327455 1004 solver.cpp:406] Test net output #29: loss/loss08 = 0.303048 (* 0.0454545 = 0.0137749 loss) | |
| I0407 15:40:54.327468 1004 solver.cpp:406] Test net output #30: loss/loss09 = 0.0826192 (* 0.0454545 = 0.00375542 loss) | |
| I0407 15:40:54.327482 1004 solver.cpp:406] Test net output #31: loss/loss10 = 0.0390088 (* 0.0454545 = 0.00177313 loss) | |
| I0407 15:40:54.327497 1004 solver.cpp:406] Test net output #32: loss/loss11 = 0.00405705 (* 0.0454545 = 0.000184412 loss) | |
| I0407 15:40:54.327509 1004 solver.cpp:406] Test net output #33: loss/loss12 = 0.00404525 (* 0.0454545 = 0.000183875 loss) | |
| I0407 15:40:54.327523 1004 solver.cpp:406] Test net output #34: loss/loss13 = 0.00403744 (* 0.0454545 = 0.00018352 loss) | |
| I0407 15:40:54.327538 1004 solver.cpp:406] Test net output #35: loss/loss14 = 0.00405754 (* 0.0454545 = 0.000184434 loss) | |
| I0407 15:40:54.327550 1004 solver.cpp:406] Test net output #36: loss/loss15 = 0.00406262 (* 0.0454545 = 0.000184665 loss) | |
| I0407 15:40:54.327564 1004 solver.cpp:406] Test net output #37: loss/loss16 = 0.00404979 (* 0.0454545 = 0.000184081 loss) | |
| I0407 15:40:54.327577 1004 solver.cpp:406] Test net output #38: loss/loss17 = 0.00401816 (* 0.0454545 = 0.000182644 loss) | |
| I0407 15:40:54.327623 1004 solver.cpp:406] Test net output #39: loss/loss18 = 0.00403182 (* 0.0454545 = 0.000183265 loss) | |
| I0407 15:40:54.327639 1004 solver.cpp:406] Test net output #40: loss/loss19 = 0.00402501 (* 0.0454545 = 0.000182955 loss) | |
| I0407 15:40:54.327653 1004 solver.cpp:406] Test net output #41: loss/loss20 = 0.00402714 (* 0.0454545 = 0.000183052 loss) | |
| I0407 15:40:54.327667 1004 solver.cpp:406] Test net output #42: loss/loss21 = 0.00401767 (* 0.0454545 = 0.000182621 loss) | |
| I0407 15:40:54.327682 1004 solver.cpp:406] Test net output #43: loss/loss22 = 0.00402398 (* 0.0454545 = 0.000182908 loss) | |
| I0407 15:40:54.327692 1004 solver.cpp:406] Test net output #44: total_accuracy = 0 | |
| I0407 15:40:54.327704 1004 solver.cpp:406] Test net output #45: total_confidence = 1.24701e-05 | |
| I0407 15:40:54.349316 1004 solver.cpp:229] Iteration 20000, loss = 1.07615 | |
| I0407 15:40:54.349354 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:40:54.349371 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.125 | |
| I0407 15:40:54.349383 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 15:40:54.349395 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 15:40:54.349407 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 15:40:54.349421 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 15:40:54.349431 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 15:40:54.349443 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 15:40:54.349455 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:40:54.349467 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 15:40:54.349479 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:40:54.349490 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:40:54.349503 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:40:54.349514 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:40:54.349524 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:40:54.349536 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:40:54.349547 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:40:54.349560 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:40:54.349571 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:40:54.349582 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:40:54.349594 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:40:54.349609 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:40:54.349624 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.91329 (* 0.0454545 = 0.177877 loss) | |
| I0407 15:40:54.349638 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.85622 (* 0.0454545 = 0.175283 loss) | |
| I0407 15:40:54.349653 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.80051 (* 0.0454545 = 0.172751 loss) | |
| I0407 15:40:54.349666 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.68051 (* 0.0454545 = 0.167296 loss) | |
| I0407 15:40:54.349680 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.26919 (* 0.0454545 = 0.148599 loss) | |
| I0407 15:40:54.349694 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.9391 (* 0.0454545 = 0.133595 loss) | |
| I0407 15:40:54.349707 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.39771 (* 0.0454545 = 0.0635322 loss) | |
| I0407 15:40:54.349721 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.724578 (* 0.0454545 = 0.0329354 loss) | |
| I0407 15:40:54.349735 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.358094 (* 0.0454545 = 0.016277 loss) | |
| I0407 15:40:54.349750 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.398325 (* 0.0454545 = 0.0181057 loss) | |
| I0407 15:40:54.349781 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000401993 (* 0.0454545 = 1.82724e-05 loss) | |
| I0407 15:40:54.349797 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000398594 (* 0.0454545 = 1.81179e-05 loss) | |
| I0407 15:40:54.349812 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000397522 (* 0.0454545 = 1.80692e-05 loss) | |
| I0407 15:40:54.349825 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000410478 (* 0.0454545 = 1.86581e-05 loss) | |
| I0407 15:40:54.349839 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000388332 (* 0.0454545 = 1.76514e-05 loss) | |
| I0407 15:40:54.349853 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000379139 (* 0.0454545 = 1.72336e-05 loss) | |
| I0407 15:40:54.349867 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.00037536 (* 0.0454545 = 1.70618e-05 loss) | |
| I0407 15:40:54.349881 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000383943 (* 0.0454545 = 1.74519e-05 loss) | |
| I0407 15:40:54.349895 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00041199 (* 0.0454545 = 1.87268e-05 loss) | |
| I0407 15:40:54.349910 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000388058 (* 0.0454545 = 1.7639e-05 loss) | |
| I0407 15:40:54.349925 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000388064 (* 0.0454545 = 1.76393e-05 loss) | |
| I0407 15:40:54.349938 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00039514 (* 0.0454545 = 1.79609e-05 loss) | |
| I0407 15:40:54.349951 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:40:54.349961 1004 solver.cpp:245] Train net output #45: total_confidence = 6.92117e-05 | |
| I0407 15:40:54.349977 1004 sgd_solver.cpp:106] Iteration 20000, lr = 0.00096 | |
| I0407 15:41:32.027597 1004 solver.cpp:229] Iteration 20500, loss = 1.08431 | |
| I0407 15:41:32.027706 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:41:32.027726 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:41:32.027740 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:41:32.027751 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 15:41:32.027765 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.3125 | |
| I0407 15:41:32.027776 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.6875 | |
| I0407 15:41:32.027788 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.875 | |
| I0407 15:41:32.027801 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 15:41:32.027812 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:41:32.027824 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:41:32.027835 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:41:32.027848 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:41:32.027859 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:41:32.027870 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:41:32.027883 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:41:32.027894 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:41:32.027906 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:41:32.027920 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:41:32.027932 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:41:32.027945 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:41:32.027956 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:41:32.027968 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:41:32.027984 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.81035 (* 0.0454545 = 0.173198 loss) | |
| I0407 15:41:32.027998 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.72645 (* 0.0454545 = 0.169384 loss) | |
| I0407 15:41:32.028012 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.93784 (* 0.0454545 = 0.178993 loss) | |
| I0407 15:41:32.028026 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.91011 (* 0.0454545 = 0.177732 loss) | |
| I0407 15:41:32.028040 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.10472 (* 0.0454545 = 0.141123 loss) | |
| I0407 15:41:32.028053 1004 solver.cpp:245] Train net output #27: loss/loss06 = 1.80327 (* 0.0454545 = 0.0819668 loss) | |
| I0407 15:41:32.028067 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.741545 (* 0.0454545 = 0.0337066 loss) | |
| I0407 15:41:32.028081 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.400733 (* 0.0454545 = 0.0182152 loss) | |
| I0407 15:41:32.028095 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.398378 (* 0.0454545 = 0.0181081 loss) | |
| I0407 15:41:32.028110 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0218711 (* 0.0454545 = 0.000994141 loss) | |
| I0407 15:41:32.028123 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000605766 (* 0.0454545 = 2.75348e-05 loss) | |
| I0407 15:41:32.028138 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000621386 (* 0.0454545 = 2.82448e-05 loss) | |
| I0407 15:41:32.028152 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000612837 (* 0.0454545 = 2.78562e-05 loss) | |
| I0407 15:41:32.028167 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000640985 (* 0.0454545 = 2.91357e-05 loss) | |
| I0407 15:41:32.028182 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000655398 (* 0.0454545 = 2.97908e-05 loss) | |
| I0407 15:41:32.028195 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000591966 (* 0.0454545 = 2.69076e-05 loss) | |
| I0407 15:41:32.028209 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000636775 (* 0.0454545 = 2.89443e-05 loss) | |
| I0407 15:41:32.028240 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000633585 (* 0.0454545 = 2.87993e-05 loss) | |
| I0407 15:41:32.028255 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000619527 (* 0.0454545 = 2.81603e-05 loss) | |
| I0407 15:41:32.028270 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000615565 (* 0.0454545 = 2.79802e-05 loss) | |
| I0407 15:41:32.028285 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000562908 (* 0.0454545 = 2.55867e-05 loss) | |
| I0407 15:41:32.028298 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00059083 (* 0.0454545 = 2.68559e-05 loss) | |
| I0407 15:41:32.028311 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:41:32.028321 1004 solver.cpp:245] Train net output #45: total_confidence = 2.2508e-05 | |
| I0407 15:41:32.028334 1004 sgd_solver.cpp:106] Iteration 20500, lr = 0.000959 | |
| I0407 15:42:10.368573 1004 solver.cpp:229] Iteration 21000, loss = 1.08763 | |
| I0407 15:42:10.368705 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:42:10.368724 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:42:10.368737 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:42:10.368749 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 15:42:10.368762 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0 | |
| I0407 15:42:10.368772 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 15:42:10.368785 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 15:42:10.368796 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 15:42:10.368808 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:42:10.368824 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:42:10.368835 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:42:10.368847 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:42:10.368859 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:42:10.368870 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:42:10.368881 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:42:10.368892 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:42:10.368904 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:42:10.368916 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:42:10.368927 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:42:10.368938 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:42:10.368949 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:42:10.368960 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:42:10.368976 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.52598 (* 0.0454545 = 0.160272 loss) | |
| I0407 15:42:10.368990 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.62313 (* 0.0454545 = 0.164688 loss) | |
| I0407 15:42:10.369004 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.85968 (* 0.0454545 = 0.17544 loss) | |
| I0407 15:42:10.369019 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.70942 (* 0.0454545 = 0.16861 loss) | |
| I0407 15:42:10.369032 1004 solver.cpp:245] Train net output #26: loss/loss05 = 4.05471 (* 0.0454545 = 0.184305 loss) | |
| I0407 15:42:10.369045 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.97538 (* 0.0454545 = 0.135244 loss) | |
| I0407 15:42:10.369060 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.43355 (* 0.0454545 = 0.0651615 loss) | |
| I0407 15:42:10.369076 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.482961 (* 0.0454545 = 0.0219528 loss) | |
| I0407 15:42:10.369091 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0720939 (* 0.0454545 = 0.003277 loss) | |
| I0407 15:42:10.369104 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0358988 (* 0.0454545 = 0.00163176 loss) | |
| I0407 15:42:10.369118 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000729807 (* 0.0454545 = 3.3173e-05 loss) | |
| I0407 15:42:10.369132 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000726456 (* 0.0454545 = 3.30207e-05 loss) | |
| I0407 15:42:10.369146 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000727806 (* 0.0454545 = 3.30821e-05 loss) | |
| I0407 15:42:10.369165 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000741145 (* 0.0454545 = 3.36884e-05 loss) | |
| I0407 15:42:10.369194 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000744749 (* 0.0454545 = 3.38522e-05 loss) | |
| I0407 15:42:10.369215 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000709213 (* 0.0454545 = 3.22369e-05 loss) | |
| I0407 15:42:10.369230 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000697183 (* 0.0454545 = 3.16901e-05 loss) | |
| I0407 15:42:10.369272 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000707928 (* 0.0454545 = 3.21785e-05 loss) | |
| I0407 15:42:10.369289 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000704863 (* 0.0454545 = 3.20392e-05 loss) | |
| I0407 15:42:10.369303 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000721039 (* 0.0454545 = 3.27745e-05 loss) | |
| I0407 15:42:10.369318 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000709627 (* 0.0454545 = 3.22558e-05 loss) | |
| I0407 15:42:10.369331 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000716841 (* 0.0454545 = 3.25837e-05 loss) | |
| I0407 15:42:10.369343 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:42:10.369355 1004 solver.cpp:245] Train net output #45: total_confidence = 8.50067e-07 | |
| I0407 15:42:10.369369 1004 sgd_solver.cpp:106] Iteration 21000, lr = 0.000958 | |
| I0407 15:42:48.509271 1004 solver.cpp:229] Iteration 21500, loss = 1.08965 | |
| I0407 15:42:48.509383 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 15:42:48.509403 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.1875 | |
| I0407 15:42:48.509416 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 15:42:48.509429 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 15:42:48.509441 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.3125 | |
| I0407 15:42:48.509454 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 15:42:48.509466 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.625 | |
| I0407 15:42:48.509479 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 15:42:48.509490 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:42:48.509502 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:42:48.509515 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:42:48.509526 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:42:48.509537 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:42:48.509549 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:42:48.509560 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:42:48.509572 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:42:48.509583 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:42:48.509595 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:42:48.509606 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:42:48.509618 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:42:48.509630 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:42:48.509641 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:42:48.509657 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.64795 (* 0.0454545 = 0.165816 loss) | |
| I0407 15:42:48.509671 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.50048 (* 0.0454545 = 0.159113 loss) | |
| I0407 15:42:48.509685 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.85244 (* 0.0454545 = 0.175111 loss) | |
| I0407 15:42:48.509699 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.54343 (* 0.0454545 = 0.161065 loss) | |
| I0407 15:42:48.509713 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.16136 (* 0.0454545 = 0.143698 loss) | |
| I0407 15:42:48.509727 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.13915 (* 0.0454545 = 0.142689 loss) | |
| I0407 15:42:48.509742 1004 solver.cpp:245] Train net output #28: loss/loss07 = 2.28123 (* 0.0454545 = 0.103692 loss) | |
| I0407 15:42:48.509755 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.08867 (* 0.0454545 = 0.0494848 loss) | |
| I0407 15:42:48.509769 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.454725 (* 0.0454545 = 0.0206693 loss) | |
| I0407 15:42:48.509783 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0106964 (* 0.0454545 = 0.000486198 loss) | |
| I0407 15:42:48.509799 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000172531 (* 0.0454545 = 7.84231e-06 loss) | |
| I0407 15:42:48.509812 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000169875 (* 0.0454545 = 7.72158e-06 loss) | |
| I0407 15:42:48.509826 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000165751 (* 0.0454545 = 7.53415e-06 loss) | |
| I0407 15:42:48.509840 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000160479 (* 0.0454545 = 7.29448e-06 loss) | |
| I0407 15:42:48.509855 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000160129 (* 0.0454545 = 7.27857e-06 loss) | |
| I0407 15:42:48.509868 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000164388 (* 0.0454545 = 7.4722e-06 loss) | |
| I0407 15:42:48.509883 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000160599 (* 0.0454545 = 7.29994e-06 loss) | |
| I0407 15:42:48.509913 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000158724 (* 0.0454545 = 7.21471e-06 loss) | |
| I0407 15:42:48.509932 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00015106 (* 0.0454545 = 6.86638e-06 loss) | |
| I0407 15:42:48.509946 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000153371 (* 0.0454545 = 6.97141e-06 loss) | |
| I0407 15:42:48.509960 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000155495 (* 0.0454545 = 7.06797e-06 loss) | |
| I0407 15:42:48.509974 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000166304 (* 0.0454545 = 7.55929e-06 loss) | |
| I0407 15:42:48.509986 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:42:48.509997 1004 solver.cpp:245] Train net output #45: total_confidence = 3.07369e-05 | |
| I0407 15:42:48.510011 1004 sgd_solver.cpp:106] Iteration 21500, lr = 0.000957 | |
| I0407 15:43:26.552251 1004 solver.cpp:229] Iteration 22000, loss = 1.08334 | |
| I0407 15:43:26.552378 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:43:26.552398 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:43:26.552412 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:43:26.552423 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 15:43:26.552435 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 15:43:26.552448 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5 | |
| I0407 15:43:26.552459 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 15:43:26.552471 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 15:43:26.552484 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:43:26.552495 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:43:26.552506 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:43:26.552518 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:43:26.552530 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:43:26.552541 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:43:26.552553 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:43:26.552564 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:43:26.552575 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:43:26.552587 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:43:26.552598 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:43:26.552610 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:43:26.552621 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:43:26.552634 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:43:26.552649 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.31518 (* 0.0454545 = 0.15069 loss) | |
| I0407 15:43:26.552664 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.61961 (* 0.0454545 = 0.164528 loss) | |
| I0407 15:43:26.552677 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.65201 (* 0.0454545 = 0.166001 loss) | |
| I0407 15:43:26.552691 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.34642 (* 0.0454545 = 0.15211 loss) | |
| I0407 15:43:26.552706 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.10608 (* 0.0454545 = 0.141186 loss) | |
| I0407 15:43:26.552718 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.46291 (* 0.0454545 = 0.11195 loss) | |
| I0407 15:43:26.552732 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.25644 (* 0.0454545 = 0.0571108 loss) | |
| I0407 15:43:26.552747 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.816105 (* 0.0454545 = 0.0370957 loss) | |
| I0407 15:43:26.552760 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.112705 (* 0.0454545 = 0.00512293 loss) | |
| I0407 15:43:26.552774 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0806711 (* 0.0454545 = 0.00366687 loss) | |
| I0407 15:43:26.552788 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.0275626 (* 0.0454545 = 0.00125284 loss) | |
| I0407 15:43:26.552803 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.0284023 (* 0.0454545 = 0.00129101 loss) | |
| I0407 15:43:26.552816 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.0271624 (* 0.0454545 = 0.00123465 loss) | |
| I0407 15:43:26.552830 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.0278031 (* 0.0454545 = 0.00126378 loss) | |
| I0407 15:43:26.552845 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.028676 (* 0.0454545 = 0.00130345 loss) | |
| I0407 15:43:26.552858 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.0271057 (* 0.0454545 = 0.00123208 loss) | |
| I0407 15:43:26.552872 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.0274713 (* 0.0454545 = 0.0012487 loss) | |
| I0407 15:43:26.553104 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.0278587 (* 0.0454545 = 0.00126631 loss) | |
| I0407 15:43:26.553122 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.0274615 (* 0.0454545 = 0.00124825 loss) | |
| I0407 15:43:26.553135 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.027672 (* 0.0454545 = 0.00125782 loss) | |
| I0407 15:43:26.553150 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.0281047 (* 0.0454545 = 0.00127749 loss) | |
| I0407 15:43:26.553164 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.0279586 (* 0.0454545 = 0.00127085 loss) | |
| I0407 15:43:26.553176 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:43:26.553187 1004 solver.cpp:245] Train net output #45: total_confidence = 4.10539e-05 | |
| I0407 15:43:26.553201 1004 sgd_solver.cpp:106] Iteration 22000, lr = 0.000956 | |
| I0407 15:44:04.693419 1004 solver.cpp:229] Iteration 22500, loss = 1.07468 | |
| I0407 15:44:04.693542 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:44:04.693563 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:44:04.693577 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 15:44:04.693588 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 15:44:04.693600 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 15:44:04.693613 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 15:44:04.693624 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.625 | |
| I0407 15:44:04.693636 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 15:44:04.693648 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:44:04.693660 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:44:04.693672 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:44:04.693683 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:44:04.693696 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:44:04.693706 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:44:04.693718 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:44:04.693730 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:44:04.693742 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:44:04.693753 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:44:04.693764 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:44:04.693775 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:44:04.693788 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:44:04.693799 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:44:04.693814 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.62868 (* 0.0454545 = 0.16494 loss) | |
| I0407 15:44:04.693830 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.88757 (* 0.0454545 = 0.176708 loss) | |
| I0407 15:44:04.693843 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.84 (* 0.0454545 = 0.174546 loss) | |
| I0407 15:44:04.693858 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.75873 (* 0.0454545 = 0.170851 loss) | |
| I0407 15:44:04.693871 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.46444 (* 0.0454545 = 0.157475 loss) | |
| I0407 15:44:04.693886 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.84553 (* 0.0454545 = 0.129342 loss) | |
| I0407 15:44:04.693899 1004 solver.cpp:245] Train net output #28: loss/loss07 = 2.02099 (* 0.0454545 = 0.091863 loss) | |
| I0407 15:44:04.693913 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.425595 (* 0.0454545 = 0.0193452 loss) | |
| I0407 15:44:04.693930 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.054357 (* 0.0454545 = 0.00247077 loss) | |
| I0407 15:44:04.693944 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0195722 (* 0.0454545 = 0.000889644 loss) | |
| I0407 15:44:04.693959 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000580519 (* 0.0454545 = 2.63872e-05 loss) | |
| I0407 15:44:04.693974 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000560732 (* 0.0454545 = 2.54878e-05 loss) | |
| I0407 15:44:04.693987 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.00056432 (* 0.0454545 = 2.56509e-05 loss) | |
| I0407 15:44:04.694001 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000563121 (* 0.0454545 = 2.55964e-05 loss) | |
| I0407 15:44:04.694015 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000589107 (* 0.0454545 = 2.67776e-05 loss) | |
| I0407 15:44:04.694030 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000576552 (* 0.0454545 = 2.62069e-05 loss) | |
| I0407 15:44:04.694043 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000552784 (* 0.0454545 = 2.51265e-05 loss) | |
| I0407 15:44:04.694074 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000572945 (* 0.0454545 = 2.60429e-05 loss) | |
| I0407 15:44:04.694090 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000573075 (* 0.0454545 = 2.60489e-05 loss) | |
| I0407 15:44:04.694104 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000563499 (* 0.0454545 = 2.56136e-05 loss) | |
| I0407 15:44:04.694118 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000557973 (* 0.0454545 = 2.53624e-05 loss) | |
| I0407 15:44:04.694133 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000559117 (* 0.0454545 = 2.54144e-05 loss) | |
| I0407 15:44:04.694144 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:44:04.694155 1004 solver.cpp:245] Train net output #45: total_confidence = 2.42567e-06 | |
| I0407 15:44:04.694169 1004 sgd_solver.cpp:106] Iteration 22500, lr = 0.000955 | |
| I0407 15:44:42.976872 1004 solver.cpp:229] Iteration 23000, loss = 1.07296 | |
| I0407 15:44:42.977010 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 15:44:42.977030 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.125 | |
| I0407 15:44:42.977043 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:44:42.977056 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 15:44:42.977067 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 15:44:42.977083 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 15:44:42.977095 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 15:44:42.977108 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 15:44:42.977119 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.875 | |
| I0407 15:44:42.977131 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 15:44:42.977144 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:44:42.977155 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:44:42.977167 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:44:42.977179 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:44:42.977190 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:44:42.977202 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:44:42.977213 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:44:42.977226 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:44:42.977236 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:44:42.977248 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:44:42.977260 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:44:42.977272 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:44:42.977288 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.77118 (* 0.0454545 = 0.171417 loss) | |
| I0407 15:44:42.977303 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.93941 (* 0.0454545 = 0.179064 loss) | |
| I0407 15:44:42.977318 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.53814 (* 0.0454545 = 0.160824 loss) | |
| I0407 15:44:42.977331 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.85825 (* 0.0454545 = 0.175375 loss) | |
| I0407 15:44:42.977344 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.52811 (* 0.0454545 = 0.160368 loss) | |
| I0407 15:44:42.977360 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.68377 (* 0.0454545 = 0.12199 loss) | |
| I0407 15:44:42.977373 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.69377 (* 0.0454545 = 0.0769898 loss) | |
| I0407 15:44:42.977386 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.07924 (* 0.0454545 = 0.0490565 loss) | |
| I0407 15:44:42.977401 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.723469 (* 0.0454545 = 0.032885 loss) | |
| I0407 15:44:42.977414 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.438806 (* 0.0454545 = 0.0199457 loss) | |
| I0407 15:44:42.977429 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000754934 (* 0.0454545 = 3.43152e-05 loss) | |
| I0407 15:44:42.977443 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00076484 (* 0.0454545 = 3.47655e-05 loss) | |
| I0407 15:44:42.977458 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000742242 (* 0.0454545 = 3.37383e-05 loss) | |
| I0407 15:44:42.977471 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000776376 (* 0.0454545 = 3.52898e-05 loss) | |
| I0407 15:44:42.977486 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000745308 (* 0.0454545 = 3.38776e-05 loss) | |
| I0407 15:44:42.977500 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000751012 (* 0.0454545 = 3.41369e-05 loss) | |
| I0407 15:44:42.977514 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000714805 (* 0.0454545 = 3.24911e-05 loss) | |
| I0407 15:44:42.977541 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.00073006 (* 0.0454545 = 3.31845e-05 loss) | |
| I0407 15:44:42.977556 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000769827 (* 0.0454545 = 3.49922e-05 loss) | |
| I0407 15:44:42.977571 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000755422 (* 0.0454545 = 3.43374e-05 loss) | |
| I0407 15:44:42.977586 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000689701 (* 0.0454545 = 3.135e-05 loss) | |
| I0407 15:44:42.977599 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000701869 (* 0.0454545 = 3.19031e-05 loss) | |
| I0407 15:44:42.977612 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:44:42.977623 1004 solver.cpp:245] Train net output #45: total_confidence = 3.77891e-06 | |
| I0407 15:44:42.977637 1004 sgd_solver.cpp:106] Iteration 23000, lr = 0.000954 | |
| I0407 15:45:21.169178 1004 solver.cpp:229] Iteration 23500, loss = 1.07605 | |
| I0407 15:45:21.169379 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 15:45:21.169400 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:45:21.169414 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 15:45:21.169426 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 15:45:21.169438 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 15:45:21.169450 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 15:45:21.169462 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 15:45:21.169474 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 15:45:21.169486 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:45:21.169498 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 15:45:21.169510 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:45:21.169523 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:45:21.169534 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:45:21.169546 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:45:21.169558 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:45:21.169569 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:45:21.169581 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:45:21.169594 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:45:21.169605 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:45:21.169616 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:45:21.169628 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:45:21.169639 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:45:21.169656 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.35174 (* 0.0454545 = 0.152352 loss) | |
| I0407 15:45:21.169669 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.54718 (* 0.0454545 = 0.161235 loss) | |
| I0407 15:45:21.169683 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.68402 (* 0.0454545 = 0.167455 loss) | |
| I0407 15:45:21.169698 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.55728 (* 0.0454545 = 0.161695 loss) | |
| I0407 15:45:21.169713 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.2658 (* 0.0454545 = 0.148445 loss) | |
| I0407 15:45:21.169726 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.95821 (* 0.0454545 = 0.134464 loss) | |
| I0407 15:45:21.169740 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.55368 (* 0.0454545 = 0.070622 loss) | |
| I0407 15:45:21.169754 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.640817 (* 0.0454545 = 0.029128 loss) | |
| I0407 15:45:21.169767 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.366021 (* 0.0454545 = 0.0166373 loss) | |
| I0407 15:45:21.169781 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.406131 (* 0.0454545 = 0.0184605 loss) | |
| I0407 15:45:21.169796 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.00143234 (* 0.0454545 = 6.51065e-05 loss) | |
| I0407 15:45:21.169811 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00144089 (* 0.0454545 = 6.54949e-05 loss) | |
| I0407 15:45:21.169826 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.001459 (* 0.0454545 = 6.6318e-05 loss) | |
| I0407 15:45:21.169839 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00131343 (* 0.0454545 = 5.97012e-05 loss) | |
| I0407 15:45:21.169853 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.00133136 (* 0.0454545 = 6.05165e-05 loss) | |
| I0407 15:45:21.169868 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.00139187 (* 0.0454545 = 6.32668e-05 loss) | |
| I0407 15:45:21.169883 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.00137941 (* 0.0454545 = 6.27003e-05 loss) | |
| I0407 15:45:21.169914 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.00134327 (* 0.0454545 = 6.10576e-05 loss) | |
| I0407 15:45:21.169932 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00134008 (* 0.0454545 = 6.09129e-05 loss) | |
| I0407 15:45:21.169947 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.00139226 (* 0.0454545 = 6.32847e-05 loss) | |
| I0407 15:45:21.169961 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00133491 (* 0.0454545 = 6.06775e-05 loss) | |
| I0407 15:45:21.169975 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00132557 (* 0.0454545 = 6.02534e-05 loss) | |
| I0407 15:45:21.169987 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:45:21.169999 1004 solver.cpp:245] Train net output #45: total_confidence = 2.79743e-06 | |
| I0407 15:45:21.170012 1004 sgd_solver.cpp:106] Iteration 23500, lr = 0.000953 | |
| I0407 15:45:59.563704 1004 solver.cpp:229] Iteration 24000, loss = 1.07627 | |
| I0407 15:45:59.563827 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:45:59.563856 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:45:59.563879 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 15:45:59.563900 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 15:45:59.563927 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.3125 | |
| I0407 15:45:59.563951 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5 | |
| I0407 15:45:59.563971 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 15:45:59.563992 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 15:45:59.564013 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:45:59.564033 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:45:59.564055 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:45:59.564076 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:45:59.564097 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:45:59.564117 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:45:59.564138 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:45:59.564159 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:45:59.564179 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:45:59.564200 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:45:59.564220 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:45:59.564242 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:45:59.564265 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:45:59.564286 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:45:59.564312 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.80347 (* 0.0454545 = 0.172885 loss) | |
| I0407 15:45:59.564339 1004 solver.cpp:245] Train net output #23: loss/loss02 = 4.0081 (* 0.0454545 = 0.182186 loss) | |
| I0407 15:45:59.564364 1004 solver.cpp:245] Train net output #24: loss/loss03 = 4.08794 (* 0.0454545 = 0.185815 loss) | |
| I0407 15:45:59.564389 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.76314 (* 0.0454545 = 0.171052 loss) | |
| I0407 15:45:59.564414 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.50635 (* 0.0454545 = 0.15938 loss) | |
| I0407 15:45:59.564441 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.80167 (* 0.0454545 = 0.127349 loss) | |
| I0407 15:45:59.564467 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.6644 (* 0.0454545 = 0.0756546 loss) | |
| I0407 15:45:59.564492 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.781481 (* 0.0454545 = 0.0355219 loss) | |
| I0407 15:45:59.564519 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0203998 (* 0.0454545 = 0.000927266 loss) | |
| I0407 15:45:59.564548 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.00654289 (* 0.0454545 = 0.000297404 loss) | |
| I0407 15:45:59.564574 1004 solver.cpp:245] Train net output #32: loss/loss11 = 4.99445e-05 (* 0.0454545 = 2.27021e-06 loss) | |
| I0407 15:45:59.564599 1004 solver.cpp:245] Train net output #33: loss/loss12 = 4.94153e-05 (* 0.0454545 = 2.24615e-06 loss) | |
| I0407 15:45:59.564625 1004 solver.cpp:245] Train net output #34: loss/loss13 = 4.97103e-05 (* 0.0454545 = 2.25956e-06 loss) | |
| I0407 15:45:59.564651 1004 solver.cpp:245] Train net output #35: loss/loss14 = 4.97283e-05 (* 0.0454545 = 2.26038e-06 loss) | |
| I0407 15:45:59.564676 1004 solver.cpp:245] Train net output #36: loss/loss15 = 5.12005e-05 (* 0.0454545 = 2.3273e-06 loss) | |
| I0407 15:45:59.564700 1004 solver.cpp:245] Train net output #37: loss/loss16 = 4.76038e-05 (* 0.0454545 = 2.16381e-06 loss) | |
| I0407 15:45:59.564725 1004 solver.cpp:245] Train net output #38: loss/loss17 = 4.9684e-05 (* 0.0454545 = 2.25836e-06 loss) | |
| I0407 15:45:59.564771 1004 solver.cpp:245] Train net output #39: loss/loss18 = 4.76786e-05 (* 0.0454545 = 2.16721e-06 loss) | |
| I0407 15:45:59.564797 1004 solver.cpp:245] Train net output #40: loss/loss19 = 4.87523e-05 (* 0.0454545 = 2.21601e-06 loss) | |
| I0407 15:45:59.564823 1004 solver.cpp:245] Train net output #41: loss/loss20 = 4.57522e-05 (* 0.0454545 = 2.07964e-06 loss) | |
| I0407 15:45:59.564852 1004 solver.cpp:245] Train net output #42: loss/loss21 = 4.65087e-05 (* 0.0454545 = 2.11403e-06 loss) | |
| I0407 15:45:59.564878 1004 solver.cpp:245] Train net output #43: loss/loss22 = 4.74139e-05 (* 0.0454545 = 2.15518e-06 loss) | |
| I0407 15:45:59.564903 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:45:59.564924 1004 solver.cpp:245] Train net output #45: total_confidence = 1.14511e-05 | |
| I0407 15:45:59.564945 1004 sgd_solver.cpp:106] Iteration 24000, lr = 0.000952 | |
| I0407 15:46:37.875738 1004 solver.cpp:229] Iteration 24500, loss = 1.08052 | |
| I0407 15:46:37.875851 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 15:46:37.875880 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:46:37.875902 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:46:37.875923 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 15:46:37.875946 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 15:46:37.875967 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 15:46:37.875989 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.875 | |
| I0407 15:46:37.876011 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 15:46:37.876032 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:46:37.876054 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:46:37.876077 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:46:37.876098 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:46:37.876119 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:46:37.876142 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:46:37.876163 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:46:37.876183 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:46:37.876204 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:46:37.876225 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:46:37.876245 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:46:37.876266 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:46:37.876286 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:46:37.876307 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:46:37.876333 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.48335 (* 0.0454545 = 0.158334 loss) | |
| I0407 15:46:37.876363 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.59668 (* 0.0454545 = 0.163486 loss) | |
| I0407 15:46:37.876389 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.784 (* 0.0454545 = 0.172 loss) | |
| I0407 15:46:37.876415 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.62248 (* 0.0454545 = 0.164658 loss) | |
| I0407 15:46:37.876440 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.24361 (* 0.0454545 = 0.147437 loss) | |
| I0407 15:46:37.876464 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.58142 (* 0.0454545 = 0.117337 loss) | |
| I0407 15:46:37.876489 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.87465 (* 0.0454545 = 0.0397568 loss) | |
| I0407 15:46:37.876515 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.735542 (* 0.0454545 = 0.0334338 loss) | |
| I0407 15:46:37.876541 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.346617 (* 0.0454545 = 0.0157553 loss) | |
| I0407 15:46:37.876566 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0258701 (* 0.0454545 = 0.00117591 loss) | |
| I0407 15:46:37.876593 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000541405 (* 0.0454545 = 2.46093e-05 loss) | |
| I0407 15:46:37.876619 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000548751 (* 0.0454545 = 2.49432e-05 loss) | |
| I0407 15:46:37.876646 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000583048 (* 0.0454545 = 2.65022e-05 loss) | |
| I0407 15:46:37.876673 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000547886 (* 0.0454545 = 2.49039e-05 loss) | |
| I0407 15:46:37.876698 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000543503 (* 0.0454545 = 2.47047e-05 loss) | |
| I0407 15:46:37.876724 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000562911 (* 0.0454545 = 2.55868e-05 loss) | |
| I0407 15:46:37.876749 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000523963 (* 0.0454545 = 2.38165e-05 loss) | |
| I0407 15:46:37.876796 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000545291 (* 0.0454545 = 2.47859e-05 loss) | |
| I0407 15:46:37.876822 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000556424 (* 0.0454545 = 2.5292e-05 loss) | |
| I0407 15:46:37.876852 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000540928 (* 0.0454545 = 2.45876e-05 loss) | |
| I0407 15:46:37.876878 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000544122 (* 0.0454545 = 2.47328e-05 loss) | |
| I0407 15:46:37.876904 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000550584 (* 0.0454545 = 2.50265e-05 loss) | |
| I0407 15:46:37.876926 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:46:37.876946 1004 solver.cpp:245] Train net output #45: total_confidence = 4.36404e-05 | |
| I0407 15:46:37.876968 1004 sgd_solver.cpp:106] Iteration 24500, lr = 0.000951 | |
| I0407 15:47:17.017858 1004 solver.cpp:338] Iteration 25000, Testing net (#0) | |
| I0407 15:47:25.013375 1004 solver.cpp:393] Test loss: 0.968098 | |
| I0407 15:47:25.013420 1004 solver.cpp:406] Test net output #0: loss/accuracy01 = 0.003 | |
| I0407 15:47:25.013437 1004 solver.cpp:406] Test net output #1: loss/accuracy02 = 0.06 | |
| I0407 15:47:25.013452 1004 solver.cpp:406] Test net output #2: loss/accuracy03 = 0.062 | |
| I0407 15:47:25.013463 1004 solver.cpp:406] Test net output #3: loss/accuracy04 = 0.086 | |
| I0407 15:47:25.013475 1004 solver.cpp:406] Test net output #4: loss/accuracy05 = 0.212 | |
| I0407 15:47:25.013487 1004 solver.cpp:406] Test net output #5: loss/accuracy06 = 0.501 | |
| I0407 15:47:25.013499 1004 solver.cpp:406] Test net output #6: loss/accuracy07 = 0.894 | |
| I0407 15:47:25.013510 1004 solver.cpp:406] Test net output #7: loss/accuracy08 = 0.97 | |
| I0407 15:47:25.013522 1004 solver.cpp:406] Test net output #8: loss/accuracy09 = 0.995 | |
| I0407 15:47:25.013533 1004 solver.cpp:406] Test net output #9: loss/accuracy10 = 0.998 | |
| I0407 15:47:25.013545 1004 solver.cpp:406] Test net output #10: loss/accuracy11 = 1 | |
| I0407 15:47:25.013557 1004 solver.cpp:406] Test net output #11: loss/accuracy12 = 1 | |
| I0407 15:47:25.013568 1004 solver.cpp:406] Test net output #12: loss/accuracy13 = 1 | |
| I0407 15:47:25.013579 1004 solver.cpp:406] Test net output #13: loss/accuracy14 = 1 | |
| I0407 15:47:25.013591 1004 solver.cpp:406] Test net output #14: loss/accuracy15 = 1 | |
| I0407 15:47:25.013602 1004 solver.cpp:406] Test net output #15: loss/accuracy16 = 1 | |
| I0407 15:47:25.013612 1004 solver.cpp:406] Test net output #16: loss/accuracy17 = 1 | |
| I0407 15:47:25.013623 1004 solver.cpp:406] Test net output #17: loss/accuracy18 = 1 | |
| I0407 15:47:25.013635 1004 solver.cpp:406] Test net output #18: loss/accuracy19 = 1 | |
| I0407 15:47:25.013646 1004 solver.cpp:406] Test net output #19: loss/accuracy20 = 1 | |
| I0407 15:47:25.013658 1004 solver.cpp:406] Test net output #20: loss/accuracy21 = 1 | |
| I0407 15:47:25.013669 1004 solver.cpp:406] Test net output #21: loss/accuracy22 = 1 | |
| I0407 15:47:25.013684 1004 solver.cpp:406] Test net output #22: loss/loss01 = 3.28973 (* 0.0454545 = 0.149533 loss) | |
| I0407 15:47:25.013698 1004 solver.cpp:406] Test net output #23: loss/loss02 = 3.47497 (* 0.0454545 = 0.157953 loss) | |
| I0407 15:47:25.013712 1004 solver.cpp:406] Test net output #24: loss/loss03 = 3.56847 (* 0.0454545 = 0.162203 loss) | |
| I0407 15:47:25.013725 1004 solver.cpp:406] Test net output #25: loss/loss04 = 3.54119 (* 0.0454545 = 0.160963 loss) | |
| I0407 15:47:25.013739 1004 solver.cpp:406] Test net output #26: loss/loss05 = 3.43827 (* 0.0454545 = 0.156285 loss) | |
| I0407 15:47:25.013752 1004 solver.cpp:406] Test net output #27: loss/loss06 = 2.53284 (* 0.0454545 = 0.115129 loss) | |
| I0407 15:47:25.013767 1004 solver.cpp:406] Test net output #28: loss/loss07 = 0.927547 (* 0.0454545 = 0.0421612 loss) | |
| I0407 15:47:25.013780 1004 solver.cpp:406] Test net output #29: loss/loss08 = 0.324068 (* 0.0454545 = 0.0147304 loss) | |
| I0407 15:47:25.013794 1004 solver.cpp:406] Test net output #30: loss/loss09 = 0.0915884 (* 0.0454545 = 0.00416311 loss) | |
| I0407 15:47:25.013808 1004 solver.cpp:406] Test net output #31: loss/loss10 = 0.0412606 (* 0.0454545 = 0.00187548 loss) | |
| I0407 15:47:25.013823 1004 solver.cpp:406] Test net output #32: loss/loss11 = 0.00570668 (* 0.0454545 = 0.000259395 loss) | |
| I0407 15:47:25.013836 1004 solver.cpp:406] Test net output #33: loss/loss12 = 0.00569283 (* 0.0454545 = 0.000258765 loss) | |
| I0407 15:47:25.013850 1004 solver.cpp:406] Test net output #34: loss/loss13 = 0.00569165 (* 0.0454545 = 0.000258712 loss) | |
| I0407 15:47:25.013864 1004 solver.cpp:406] Test net output #35: loss/loss14 = 0.00568742 (* 0.0454545 = 0.000258519 loss) | |
| I0407 15:47:25.013878 1004 solver.cpp:406] Test net output #36: loss/loss15 = 0.00569248 (* 0.0454545 = 0.000258749 loss) | |
| I0407 15:47:25.013892 1004 solver.cpp:406] Test net output #37: loss/loss16 = 0.00568401 (* 0.0454545 = 0.000258364 loss) | |
| I0407 15:47:25.013906 1004 solver.cpp:406] Test net output #38: loss/loss17 = 0.00567791 (* 0.0454545 = 0.000258087 loss) | |
| I0407 15:47:25.013959 1004 solver.cpp:406] Test net output #39: loss/loss18 = 0.00567857 (* 0.0454545 = 0.000258117 loss) | |
| I0407 15:47:25.013975 1004 solver.cpp:406] Test net output #40: loss/loss19 = 0.0056799 (* 0.0454545 = 0.000258177 loss) | |
| I0407 15:47:25.013989 1004 solver.cpp:406] Test net output #41: loss/loss20 = 0.00568113 (* 0.0454545 = 0.000258233 loss) | |
| I0407 15:47:25.014010 1004 solver.cpp:406] Test net output #42: loss/loss21 = 0.00567363 (* 0.0454545 = 0.000257892 loss) | |
| I0407 15:47:25.014041 1004 solver.cpp:406] Test net output #43: loss/loss22 = 0.00566655 (* 0.0454545 = 0.00025757 loss) | |
| I0407 15:47:25.014060 1004 solver.cpp:406] Test net output #44: total_accuracy = 0 | |
| I0407 15:47:25.014073 1004 solver.cpp:406] Test net output #45: total_confidence = 3.1303e-06 | |
| I0407 15:47:25.036334 1004 solver.cpp:229] Iteration 25000, loss = 1.0772 | |
| I0407 15:47:25.036370 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:47:25.036387 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:47:25.036401 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.1875 | |
| I0407 15:47:25.036413 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 15:47:25.036425 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 15:47:25.036437 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5 | |
| I0407 15:47:25.036449 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 15:47:25.036460 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 15:47:25.036478 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:47:25.036489 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:47:25.036501 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:47:25.036512 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:47:25.036525 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:47:25.036535 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:47:25.036547 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:47:25.036559 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:47:25.036571 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:47:25.036582 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:47:25.036593 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:47:25.036605 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:47:25.036617 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:47:25.036628 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:47:25.036643 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.41838 (* 0.0454545 = 0.155381 loss) | |
| I0407 15:47:25.036658 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.69567 (* 0.0454545 = 0.167985 loss) | |
| I0407 15:47:25.036675 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.5466 (* 0.0454545 = 0.161209 loss) | |
| I0407 15:47:25.036701 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.40921 (* 0.0454545 = 0.154964 loss) | |
| I0407 15:47:25.036717 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.19196 (* 0.0454545 = 0.145089 loss) | |
| I0407 15:47:25.036731 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.50108 (* 0.0454545 = 0.113686 loss) | |
| I0407 15:47:25.036746 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.51173 (* 0.0454545 = 0.0687149 loss) | |
| I0407 15:47:25.036759 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.132525 (* 0.0454545 = 0.00602388 loss) | |
| I0407 15:47:25.036773 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0606421 (* 0.0454545 = 0.00275646 loss) | |
| I0407 15:47:25.036788 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0218244 (* 0.0454545 = 0.000992017 loss) | |
| I0407 15:47:25.036819 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000612348 (* 0.0454545 = 2.7834e-05 loss) | |
| I0407 15:47:25.036835 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000598445 (* 0.0454545 = 2.7202e-05 loss) | |
| I0407 15:47:25.036850 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000571183 (* 0.0454545 = 2.59629e-05 loss) | |
| I0407 15:47:25.036864 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00057768 (* 0.0454545 = 2.62582e-05 loss) | |
| I0407 15:47:25.036878 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000619239 (* 0.0454545 = 2.81472e-05 loss) | |
| I0407 15:47:25.036892 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.00055603 (* 0.0454545 = 2.52741e-05 loss) | |
| I0407 15:47:25.036906 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000583352 (* 0.0454545 = 2.6516e-05 loss) | |
| I0407 15:47:25.036921 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000580719 (* 0.0454545 = 2.63963e-05 loss) | |
| I0407 15:47:25.036938 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000580807 (* 0.0454545 = 2.64003e-05 loss) | |
| I0407 15:47:25.036952 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000566349 (* 0.0454545 = 2.57431e-05 loss) | |
| I0407 15:47:25.036967 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000580741 (* 0.0454545 = 2.63973e-05 loss) | |
| I0407 15:47:25.036980 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00055493 (* 0.0454545 = 2.52241e-05 loss) | |
| I0407 15:47:25.036993 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:47:25.037004 1004 solver.cpp:245] Train net output #45: total_confidence = 3.14641e-06 | |
| I0407 15:47:25.037019 1004 sgd_solver.cpp:106] Iteration 25000, lr = 0.00095 | |
| I0407 15:48:02.925506 1004 solver.cpp:229] Iteration 25500, loss = 1.08308 | |
| I0407 15:48:02.925662 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.1875 | |
| I0407 15:48:02.925689 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.125 | |
| I0407 15:48:02.925710 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 15:48:02.925731 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 15:48:02.925751 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 15:48:02.925772 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 15:48:02.925794 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.625 | |
| I0407 15:48:02.925814 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 15:48:02.925835 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:48:02.925856 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:48:02.925876 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:48:02.925896 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:48:02.925916 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:48:02.925941 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:48:02.925961 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:48:02.925982 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:48:02.926002 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:48:02.926023 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:48:02.926045 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:48:02.926069 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:48:02.926089 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:48:02.926108 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:48:02.926136 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.61736 (* 0.0454545 = 0.164425 loss) | |
| I0407 15:48:02.926162 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.7802 (* 0.0454545 = 0.171827 loss) | |
| I0407 15:48:02.926187 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.71409 (* 0.0454545 = 0.168822 loss) | |
| I0407 15:48:02.926213 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.70596 (* 0.0454545 = 0.168453 loss) | |
| I0407 15:48:02.926239 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.53156 (* 0.0454545 = 0.160525 loss) | |
| I0407 15:48:02.926264 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.81591 (* 0.0454545 = 0.127996 loss) | |
| I0407 15:48:02.926288 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.93253 (* 0.0454545 = 0.0878422 loss) | |
| I0407 15:48:02.926314 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.149907 (* 0.0454545 = 0.00681394 loss) | |
| I0407 15:48:02.926340 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0470761 (* 0.0454545 = 0.00213982 loss) | |
| I0407 15:48:02.926367 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0186234 (* 0.0454545 = 0.000846518 loss) | |
| I0407 15:48:02.926394 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000622699 (* 0.0454545 = 2.83045e-05 loss) | |
| I0407 15:48:02.926420 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000587968 (* 0.0454545 = 2.67258e-05 loss) | |
| I0407 15:48:02.926447 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000553317 (* 0.0454545 = 2.51508e-05 loss) | |
| I0407 15:48:02.926472 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000594298 (* 0.0454545 = 2.70135e-05 loss) | |
| I0407 15:48:02.926498 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000588579 (* 0.0454545 = 2.67536e-05 loss) | |
| I0407 15:48:02.926524 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000586954 (* 0.0454545 = 2.66797e-05 loss) | |
| I0407 15:48:02.926549 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000560859 (* 0.0454545 = 2.54936e-05 loss) | |
| I0407 15:48:02.926599 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000571326 (* 0.0454545 = 2.59693e-05 loss) | |
| I0407 15:48:02.926625 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000565664 (* 0.0454545 = 2.5712e-05 loss) | |
| I0407 15:48:02.926651 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000577629 (* 0.0454545 = 2.62559e-05 loss) | |
| I0407 15:48:02.926681 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000583188 (* 0.0454545 = 2.65086e-05 loss) | |
| I0407 15:48:02.926707 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000581304 (* 0.0454545 = 2.64229e-05 loss) | |
| I0407 15:48:02.926728 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:48:02.926749 1004 solver.cpp:245] Train net output #45: total_confidence = 2.90867e-06 | |
| I0407 15:48:02.926774 1004 sgd_solver.cpp:106] Iteration 25500, lr = 0.000949 | |
| I0407 15:48:41.348312 1004 solver.cpp:229] Iteration 26000, loss = 1.08503 | |
| I0407 15:48:41.348445 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:48:41.348474 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:48:41.348489 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:48:41.348500 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 15:48:41.348512 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.0625 | |
| I0407 15:48:41.348531 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.1875 | |
| I0407 15:48:41.348543 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 15:48:41.348556 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 15:48:41.348567 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.875 | |
| I0407 15:48:41.348579 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 15:48:41.348592 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:48:41.348603 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:48:41.348613 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:48:41.348625 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:48:41.348636 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:48:41.348649 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:48:41.348660 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:48:41.348680 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:48:41.348691 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:48:41.348703 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:48:41.348714 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:48:41.348726 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:48:41.348742 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.66266 (* 0.0454545 = 0.166485 loss) | |
| I0407 15:48:41.348755 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.81361 (* 0.0454545 = 0.173346 loss) | |
| I0407 15:48:41.348778 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.86028 (* 0.0454545 = 0.175467 loss) | |
| I0407 15:48:41.348791 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.76582 (* 0.0454545 = 0.171174 loss) | |
| I0407 15:48:41.348805 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.8243 (* 0.0454545 = 0.173832 loss) | |
| I0407 15:48:41.348819 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.50203 (* 0.0454545 = 0.159183 loss) | |
| I0407 15:48:41.348832 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.74874 (* 0.0454545 = 0.079488 loss) | |
| I0407 15:48:41.348846 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.11549 (* 0.0454545 = 0.0507042 loss) | |
| I0407 15:48:41.348860 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.790862 (* 0.0454545 = 0.0359483 loss) | |
| I0407 15:48:41.348875 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.379572 (* 0.0454545 = 0.0172533 loss) | |
| I0407 15:48:41.348891 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000950176 (* 0.0454545 = 4.31898e-05 loss) | |
| I0407 15:48:41.348904 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000945817 (* 0.0454545 = 4.29917e-05 loss) | |
| I0407 15:48:41.348920 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.0010135 (* 0.0454545 = 4.60681e-05 loss) | |
| I0407 15:48:41.348935 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000982928 (* 0.0454545 = 4.46786e-05 loss) | |
| I0407 15:48:41.348953 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000951187 (* 0.0454545 = 4.32358e-05 loss) | |
| I0407 15:48:41.348968 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.00102914 (* 0.0454545 = 4.6779e-05 loss) | |
| I0407 15:48:41.348981 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000968186 (* 0.0454545 = 4.40085e-05 loss) | |
| I0407 15:48:41.349014 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000974301 (* 0.0454545 = 4.42864e-05 loss) | |
| I0407 15:48:41.349030 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00104701 (* 0.0454545 = 4.75913e-05 loss) | |
| I0407 15:48:41.349043 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000925128 (* 0.0454545 = 4.20513e-05 loss) | |
| I0407 15:48:41.349057 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000980245 (* 0.0454545 = 4.45566e-05 loss) | |
| I0407 15:48:41.349078 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000980843 (* 0.0454545 = 4.45838e-05 loss) | |
| I0407 15:48:41.349091 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:48:41.349102 1004 solver.cpp:245] Train net output #45: total_confidence = 1.86583e-06 | |
| I0407 15:48:41.349115 1004 sgd_solver.cpp:106] Iteration 26000, lr = 0.000948 | |
| I0407 15:49:20.034112 1004 solver.cpp:229] Iteration 26500, loss = 1.0794 | |
| I0407 15:49:20.034247 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:49:20.034266 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:49:20.034281 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:49:20.034292 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 15:49:20.034306 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 15:49:20.034317 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5 | |
| I0407 15:49:20.034329 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.625 | |
| I0407 15:49:20.034342 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 15:49:20.034353 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:49:20.034365 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 15:49:20.034378 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:49:20.034389 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:49:20.034401 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:49:20.034412 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:49:20.034425 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:49:20.034436 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:49:20.034448 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:49:20.034461 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:49:20.034472 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:49:20.034483 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:49:20.034495 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:49:20.034507 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:49:20.034523 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.7742 (* 0.0454545 = 0.171555 loss) | |
| I0407 15:49:20.034538 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.51582 (* 0.0454545 = 0.15981 loss) | |
| I0407 15:49:20.034553 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.7866 (* 0.0454545 = 0.172118 loss) | |
| I0407 15:49:20.034566 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.85961 (* 0.0454545 = 0.175437 loss) | |
| I0407 15:49:20.034580 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.32694 (* 0.0454545 = 0.151224 loss) | |
| I0407 15:49:20.034595 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.25468 (* 0.0454545 = 0.102486 loss) | |
| I0407 15:49:20.034608 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.93959 (* 0.0454545 = 0.088163 loss) | |
| I0407 15:49:20.034622 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.36235 (* 0.0454545 = 0.0164705 loss) | |
| I0407 15:49:20.034636 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.324585 (* 0.0454545 = 0.0147539 loss) | |
| I0407 15:49:20.034651 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.350881 (* 0.0454545 = 0.0159491 loss) | |
| I0407 15:49:20.034664 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000618093 (* 0.0454545 = 2.80951e-05 loss) | |
| I0407 15:49:20.034678 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00061535 (* 0.0454545 = 2.79705e-05 loss) | |
| I0407 15:49:20.034693 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000638192 (* 0.0454545 = 2.90087e-05 loss) | |
| I0407 15:49:20.034708 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00065078 (* 0.0454545 = 2.95809e-05 loss) | |
| I0407 15:49:20.034723 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000635536 (* 0.0454545 = 2.8888e-05 loss) | |
| I0407 15:49:20.034736 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000654598 (* 0.0454545 = 2.97545e-05 loss) | |
| I0407 15:49:20.034750 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000667004 (* 0.0454545 = 3.03184e-05 loss) | |
| I0407 15:49:20.034777 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000611089 (* 0.0454545 = 2.77768e-05 loss) | |
| I0407 15:49:20.034793 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000662034 (* 0.0454545 = 3.00924e-05 loss) | |
| I0407 15:49:20.034807 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000598642 (* 0.0454545 = 2.7211e-05 loss) | |
| I0407 15:49:20.034821 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000624105 (* 0.0454545 = 2.83684e-05 loss) | |
| I0407 15:49:20.034845 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000638698 (* 0.0454545 = 2.90317e-05 loss) | |
| I0407 15:49:20.034868 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:49:20.034881 1004 solver.cpp:245] Train net output #45: total_confidence = 1.08153e-05 | |
| I0407 15:49:20.034895 1004 sgd_solver.cpp:106] Iteration 26500, lr = 0.000947 | |
| I0407 15:49:58.436386 1004 solver.cpp:229] Iteration 27000, loss = 1.0741 | |
| I0407 15:49:58.436535 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 15:49:58.436554 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:49:58.436569 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:49:58.436581 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 15:49:58.436594 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.3125 | |
| I0407 15:49:58.436606 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 15:49:58.436619 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 15:49:58.436630 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 15:49:58.436642 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:49:58.436655 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:49:58.436666 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:49:58.436678 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:49:58.436691 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:49:58.436702 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:49:58.436713 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:49:58.436725 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:49:58.436738 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:49:58.436748 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:49:58.436760 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:49:58.436772 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:49:58.436784 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:49:58.436795 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:49:58.436811 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.61563 (* 0.0454545 = 0.164347 loss) | |
| I0407 15:49:58.436826 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.87796 (* 0.0454545 = 0.176271 loss) | |
| I0407 15:49:58.436841 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.69622 (* 0.0454545 = 0.16801 loss) | |
| I0407 15:49:58.436854 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.6385 (* 0.0454545 = 0.165387 loss) | |
| I0407 15:49:58.436868 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.28264 (* 0.0454545 = 0.149211 loss) | |
| I0407 15:49:58.436882 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.88318 (* 0.0454545 = 0.131054 loss) | |
| I0407 15:49:58.436898 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.29237 (* 0.0454545 = 0.0587441 loss) | |
| I0407 15:49:58.436913 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.183114 (* 0.0454545 = 0.00832337 loss) | |
| I0407 15:49:58.436930 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0775274 (* 0.0454545 = 0.00352397 loss) | |
| I0407 15:49:58.436944 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0354426 (* 0.0454545 = 0.00161103 loss) | |
| I0407 15:49:58.436959 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000985108 (* 0.0454545 = 4.47776e-05 loss) | |
| I0407 15:49:58.436974 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00101112 (* 0.0454545 = 4.59598e-05 loss) | |
| I0407 15:49:58.436987 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.00100881 (* 0.0454545 = 4.58552e-05 loss) | |
| I0407 15:49:58.437001 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00100095 (* 0.0454545 = 4.54976e-05 loss) | |
| I0407 15:49:58.437016 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.00098528 (* 0.0454545 = 4.47855e-05 loss) | |
| I0407 15:49:58.437031 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.00105102 (* 0.0454545 = 4.77736e-05 loss) | |
| I0407 15:49:58.437044 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000987604 (* 0.0454545 = 4.48911e-05 loss) | |
| I0407 15:49:58.437078 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000976225 (* 0.0454545 = 4.43739e-05 loss) | |
| I0407 15:49:58.437094 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00103221 (* 0.0454545 = 4.69186e-05 loss) | |
| I0407 15:49:58.437108 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.00107591 (* 0.0454545 = 4.8905e-05 loss) | |
| I0407 15:49:58.437124 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000978223 (* 0.0454545 = 4.44647e-05 loss) | |
| I0407 15:49:58.437137 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00101525 (* 0.0454545 = 4.61476e-05 loss) | |
| I0407 15:49:58.437150 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:49:58.437161 1004 solver.cpp:245] Train net output #45: total_confidence = 4.97174e-06 | |
| I0407 15:49:58.437176 1004 sgd_solver.cpp:106] Iteration 27000, lr = 0.000946 | |
| I0407 15:50:37.821167 1004 solver.cpp:229] Iteration 27500, loss = 1.0761 | |
| I0407 15:50:37.821279 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 15:50:37.821297 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.1875 | |
| I0407 15:50:37.821310 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:50:37.821322 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 15:50:37.821334 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 15:50:37.821347 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 15:50:37.821359 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 15:50:37.821370 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 15:50:37.821383 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:50:37.821396 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 15:50:37.821408 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:50:37.821419 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:50:37.821431 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:50:37.821442 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:50:37.821454 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:50:37.821465 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:50:37.821476 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:50:37.821487 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:50:37.821499 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:50:37.821511 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:50:37.821522 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:50:37.821534 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:50:37.821550 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.66109 (* 0.0454545 = 0.166413 loss) | |
| I0407 15:50:37.821565 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.63323 (* 0.0454545 = 0.165147 loss) | |
| I0407 15:50:37.821579 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.93549 (* 0.0454545 = 0.178886 loss) | |
| I0407 15:50:37.821593 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.7094 (* 0.0454545 = 0.168609 loss) | |
| I0407 15:50:37.821607 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.75058 (* 0.0454545 = 0.170481 loss) | |
| I0407 15:50:37.821620 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.22948 (* 0.0454545 = 0.146795 loss) | |
| I0407 15:50:37.821635 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.19307 (* 0.0454545 = 0.0542303 loss) | |
| I0407 15:50:37.821648 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.98937 (* 0.0454545 = 0.0449713 loss) | |
| I0407 15:50:37.821661 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.617438 (* 0.0454545 = 0.0280654 loss) | |
| I0407 15:50:37.821676 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.759766 (* 0.0454545 = 0.0345348 loss) | |
| I0407 15:50:37.821689 1004 solver.cpp:245] Train net output #32: loss/loss11 = 6.20223e-05 (* 0.0454545 = 2.8192e-06 loss) | |
| I0407 15:50:37.821703 1004 solver.cpp:245] Train net output #33: loss/loss12 = 6.15756e-05 (* 0.0454545 = 2.79889e-06 loss) | |
| I0407 15:50:37.821722 1004 solver.cpp:245] Train net output #34: loss/loss13 = 6.10163e-05 (* 0.0454545 = 2.77347e-06 loss) | |
| I0407 15:50:37.821751 1004 solver.cpp:245] Train net output #35: loss/loss14 = 5.94881e-05 (* 0.0454545 = 2.70401e-06 loss) | |
| I0407 15:50:37.821774 1004 solver.cpp:245] Train net output #36: loss/loss15 = 6.1195e-05 (* 0.0454545 = 2.78159e-06 loss) | |
| I0407 15:50:37.821789 1004 solver.cpp:245] Train net output #37: loss/loss16 = 5.99802e-05 (* 0.0454545 = 2.72637e-06 loss) | |
| I0407 15:50:37.821802 1004 solver.cpp:245] Train net output #38: loss/loss17 = 6.15084e-05 (* 0.0454545 = 2.79584e-06 loss) | |
| I0407 15:50:37.821835 1004 solver.cpp:245] Train net output #39: loss/loss18 = 5.83479e-05 (* 0.0454545 = 2.65218e-06 loss) | |
| I0407 15:50:37.821851 1004 solver.cpp:245] Train net output #40: loss/loss19 = 5.75016e-05 (* 0.0454545 = 2.61371e-06 loss) | |
| I0407 15:50:37.821864 1004 solver.cpp:245] Train net output #41: loss/loss20 = 5.68756e-05 (* 0.0454545 = 2.58526e-06 loss) | |
| I0407 15:50:37.821878 1004 solver.cpp:245] Train net output #42: loss/loss21 = 6.12324e-05 (* 0.0454545 = 2.78329e-06 loss) | |
| I0407 15:50:37.821892 1004 solver.cpp:245] Train net output #43: loss/loss22 = 5.92012e-05 (* 0.0454545 = 2.69097e-06 loss) | |
| I0407 15:50:37.821904 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:50:37.821916 1004 solver.cpp:245] Train net output #45: total_confidence = 6.80012e-05 | |
| I0407 15:50:37.821929 1004 sgd_solver.cpp:106] Iteration 27500, lr = 0.000945 | |
| I0407 15:51:16.969310 1004 solver.cpp:229] Iteration 28000, loss = 1.07111 | |
| I0407 15:51:16.969451 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 15:51:16.969471 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:51:16.969485 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 15:51:16.969497 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 15:51:16.969509 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 15:51:16.969522 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 15:51:16.969534 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 15:51:16.969547 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 15:51:16.969558 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:51:16.969570 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:51:16.969583 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:51:16.969594 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:51:16.969605 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:51:16.969617 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:51:16.969629 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:51:16.969640 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:51:16.969652 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:51:16.969665 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:51:16.969676 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:51:16.969687 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:51:16.969698 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:51:16.969710 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:51:16.969727 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.54415 (* 0.0454545 = 0.161098 loss) | |
| I0407 15:51:16.969741 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.92101 (* 0.0454545 = 0.178228 loss) | |
| I0407 15:51:16.969755 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.62246 (* 0.0454545 = 0.164657 loss) | |
| I0407 15:51:16.969769 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.41077 (* 0.0454545 = 0.155035 loss) | |
| I0407 15:51:16.969784 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.24128 (* 0.0454545 = 0.147331 loss) | |
| I0407 15:51:16.969796 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.9561 (* 0.0454545 = 0.134368 loss) | |
| I0407 15:51:16.969810 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.84052 (* 0.0454545 = 0.0836601 loss) | |
| I0407 15:51:16.969825 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.574834 (* 0.0454545 = 0.0261288 loss) | |
| I0407 15:51:16.969840 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0241779 (* 0.0454545 = 0.001099 loss) | |
| I0407 15:51:16.969853 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.00842603 (* 0.0454545 = 0.000383001 loss) | |
| I0407 15:51:16.969868 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000214212 (* 0.0454545 = 9.73692e-06 loss) | |
| I0407 15:51:16.969882 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00022238 (* 0.0454545 = 1.01082e-05 loss) | |
| I0407 15:51:16.969897 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000213872 (* 0.0454545 = 9.72146e-06 loss) | |
| I0407 15:51:16.969912 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000203484 (* 0.0454545 = 9.24928e-06 loss) | |
| I0407 15:51:16.969928 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000207945 (* 0.0454545 = 9.45203e-06 loss) | |
| I0407 15:51:16.969944 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000206369 (* 0.0454545 = 9.38043e-06 loss) | |
| I0407 15:51:16.969957 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000211068 (* 0.0454545 = 9.59401e-06 loss) | |
| I0407 15:51:16.969988 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000203884 (* 0.0454545 = 9.26745e-06 loss) | |
| I0407 15:51:16.970005 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000206967 (* 0.0454545 = 9.40758e-06 loss) | |
| I0407 15:51:16.970018 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000202959 (* 0.0454545 = 9.22542e-06 loss) | |
| I0407 15:51:16.970032 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000188968 (* 0.0454545 = 8.58947e-06 loss) | |
| I0407 15:51:16.970046 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000177463 (* 0.0454545 = 8.06649e-06 loss) | |
| I0407 15:51:16.970058 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:51:16.970069 1004 solver.cpp:245] Train net output #45: total_confidence = 9.88628e-05 | |
| I0407 15:51:16.970084 1004 sgd_solver.cpp:106] Iteration 28000, lr = 0.000944 | |
| I0407 15:51:55.759666 1004 solver.cpp:229] Iteration 28500, loss = 1.0723 | |
| I0407 15:51:55.759794 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:51:55.759814 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:51:55.759827 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 15:51:55.759840 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 15:51:55.759852 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.3125 | |
| I0407 15:51:55.759865 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 15:51:55.759877 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 15:51:55.759889 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 15:51:55.759902 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:51:55.759912 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:51:55.759928 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:51:55.759940 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:51:55.759953 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:51:55.759963 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:51:55.759975 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:51:55.759987 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:51:55.759999 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:51:55.760010 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:51:55.760022 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:51:55.760035 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:51:55.760046 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:51:55.760058 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:51:55.760074 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.59393 (* 0.0454545 = 0.16336 loss) | |
| I0407 15:51:55.760089 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.53685 (* 0.0454545 = 0.160766 loss) | |
| I0407 15:51:55.760102 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.43331 (* 0.0454545 = 0.15606 loss) | |
| I0407 15:51:55.760116 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.61531 (* 0.0454545 = 0.164332 loss) | |
| I0407 15:51:55.760130 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.05235 (* 0.0454545 = 0.138743 loss) | |
| I0407 15:51:55.760143 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.10563 (* 0.0454545 = 0.141165 loss) | |
| I0407 15:51:55.760157 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.49173 (* 0.0454545 = 0.0678058 loss) | |
| I0407 15:51:55.760171 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.0846963 (* 0.0454545 = 0.00384983 loss) | |
| I0407 15:51:55.760185 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0239224 (* 0.0454545 = 0.00108738 loss) | |
| I0407 15:51:55.760200 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.00896385 (* 0.0454545 = 0.000407448 loss) | |
| I0407 15:51:55.760220 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000139403 (* 0.0454545 = 6.3365e-06 loss) | |
| I0407 15:51:55.760248 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000142494 (* 0.0454545 = 6.47701e-06 loss) | |
| I0407 15:51:55.760265 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000135601 (* 0.0454545 = 6.16367e-06 loss) | |
| I0407 15:51:55.760287 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000149858 (* 0.0454545 = 6.81171e-06 loss) | |
| I0407 15:51:55.760310 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000141047 (* 0.0454545 = 6.41123e-06 loss) | |
| I0407 15:51:55.760325 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000134392 (* 0.0454545 = 6.10871e-06 loss) | |
| I0407 15:51:55.760339 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000150333 (* 0.0454545 = 6.83332e-06 loss) | |
| I0407 15:51:55.760367 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000135689 (* 0.0454545 = 6.16767e-06 loss) | |
| I0407 15:51:55.760382 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000130004 (* 0.0454545 = 5.90927e-06 loss) | |
| I0407 15:51:55.760396 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000130616 (* 0.0454545 = 5.93709e-06 loss) | |
| I0407 15:51:55.760411 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00014402 (* 0.0454545 = 6.54635e-06 loss) | |
| I0407 15:51:55.760424 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000146535 (* 0.0454545 = 6.66069e-06 loss) | |
| I0407 15:51:55.760437 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:51:55.760448 1004 solver.cpp:245] Train net output #45: total_confidence = 3.16581e-05 | |
| I0407 15:51:55.760462 1004 sgd_solver.cpp:106] Iteration 28500, lr = 0.000943 | |
| I0407 15:52:33.957574 1004 solver.cpp:229] Iteration 29000, loss = 1.08307 | |
| I0407 15:52:33.957684 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:52:33.957705 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:52:33.957717 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 15:52:33.957729 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 15:52:33.957742 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 15:52:33.957754 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.25 | |
| I0407 15:52:33.957767 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 15:52:33.957778 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 15:52:33.957790 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:52:33.957803 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:52:33.957814 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:52:33.957825 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:52:33.957837 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:52:33.957849 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:52:33.957860 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:52:33.957872 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:52:33.957885 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:52:33.957896 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:52:33.957908 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:52:33.957922 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:52:33.957934 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:52:33.957947 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:52:33.957962 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.55558 (* 0.0454545 = 0.161617 loss) | |
| I0407 15:52:33.957976 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.84579 (* 0.0454545 = 0.174809 loss) | |
| I0407 15:52:33.957990 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.93628 (* 0.0454545 = 0.178922 loss) | |
| I0407 15:52:33.958004 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.89353 (* 0.0454545 = 0.176979 loss) | |
| I0407 15:52:33.958019 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.75289 (* 0.0454545 = 0.170586 loss) | |
| I0407 15:52:33.958032 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.60895 (* 0.0454545 = 0.164043 loss) | |
| I0407 15:52:33.958045 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.96357 (* 0.0454545 = 0.0892533 loss) | |
| I0407 15:52:33.958060 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.45765 (* 0.0454545 = 0.0662569 loss) | |
| I0407 15:52:33.958073 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0538652 (* 0.0454545 = 0.00244842 loss) | |
| I0407 15:52:33.958088 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0268348 (* 0.0454545 = 0.00121976 loss) | |
| I0407 15:52:33.958102 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.00128294 (* 0.0454545 = 5.83154e-05 loss) | |
| I0407 15:52:33.958117 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00133336 (* 0.0454545 = 6.06073e-05 loss) | |
| I0407 15:52:33.958132 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.0012607 (* 0.0454545 = 5.73043e-05 loss) | |
| I0407 15:52:33.958145 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00121027 (* 0.0454545 = 5.50123e-05 loss) | |
| I0407 15:52:33.958160 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.00126827 (* 0.0454545 = 5.76485e-05 loss) | |
| I0407 15:52:33.958175 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.00122201 (* 0.0454545 = 5.55459e-05 loss) | |
| I0407 15:52:33.958189 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.0012319 (* 0.0454545 = 5.59953e-05 loss) | |
| I0407 15:52:33.958220 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.00122176 (* 0.0454545 = 5.55344e-05 loss) | |
| I0407 15:52:33.958236 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00120366 (* 0.0454545 = 5.47117e-05 loss) | |
| I0407 15:52:33.958250 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.00130164 (* 0.0454545 = 5.91653e-05 loss) | |
| I0407 15:52:33.958264 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00118457 (* 0.0454545 = 5.38439e-05 loss) | |
| I0407 15:52:33.958278 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.0011809 (* 0.0454545 = 5.36772e-05 loss) | |
| I0407 15:52:33.958292 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:52:33.958302 1004 solver.cpp:245] Train net output #45: total_confidence = 1.42784e-05 | |
| I0407 15:52:33.958315 1004 sgd_solver.cpp:106] Iteration 29000, lr = 0.000942 | |
| I0407 15:53:12.268633 1004 solver.cpp:229] Iteration 29500, loss = 1.0764 | |
| I0407 15:53:12.268746 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 15:53:12.268766 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:53:12.268780 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 15:53:12.268792 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 15:53:12.268805 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 15:53:12.268817 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5 | |
| I0407 15:53:12.268828 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.625 | |
| I0407 15:53:12.268841 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 15:53:12.268853 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.8125 | |
| I0407 15:53:12.268865 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 15:53:12.268877 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:53:12.268888 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:53:12.268900 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:53:12.268911 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:53:12.268926 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:53:12.268939 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:53:12.268950 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:53:12.268962 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:53:12.268973 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:53:12.268985 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:53:12.268997 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:53:12.269008 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:53:12.269024 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.33202 (* 0.0454545 = 0.151455 loss) | |
| I0407 15:53:12.269038 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.64571 (* 0.0454545 = 0.165714 loss) | |
| I0407 15:53:12.269052 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.47447 (* 0.0454545 = 0.157931 loss) | |
| I0407 15:53:12.269067 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.56805 (* 0.0454545 = 0.162184 loss) | |
| I0407 15:53:12.269080 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.40255 (* 0.0454545 = 0.154661 loss) | |
| I0407 15:53:12.269094 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.17219 (* 0.0454545 = 0.0987357 loss) | |
| I0407 15:53:12.269109 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.99714 (* 0.0454545 = 0.0907791 loss) | |
| I0407 15:53:12.269122 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.08808 (* 0.0454545 = 0.0494583 loss) | |
| I0407 15:53:12.269136 1004 solver.cpp:245] Train net output #30: loss/loss09 = 1.16633 (* 0.0454545 = 0.053015 loss) | |
| I0407 15:53:12.269150 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.502094 (* 0.0454545 = 0.0228224 loss) | |
| I0407 15:53:12.269165 1004 solver.cpp:245] Train net output #32: loss/loss11 = 4.94509e-05 (* 0.0454545 = 2.24777e-06 loss) | |
| I0407 15:53:12.269179 1004 solver.cpp:245] Train net output #33: loss/loss12 = 4.71698e-05 (* 0.0454545 = 2.14408e-06 loss) | |
| I0407 15:53:12.269194 1004 solver.cpp:245] Train net output #34: loss/loss13 = 5.10949e-05 (* 0.0454545 = 2.3225e-06 loss) | |
| I0407 15:53:12.269208 1004 solver.cpp:245] Train net output #35: loss/loss14 = 4.73114e-05 (* 0.0454545 = 2.15052e-06 loss) | |
| I0407 15:53:12.269222 1004 solver.cpp:245] Train net output #36: loss/loss15 = 4.87725e-05 (* 0.0454545 = 2.21693e-06 loss) | |
| I0407 15:53:12.269237 1004 solver.cpp:245] Train net output #37: loss/loss16 = 4.65251e-05 (* 0.0454545 = 2.11478e-06 loss) | |
| I0407 15:53:12.269251 1004 solver.cpp:245] Train net output #38: loss/loss17 = 4.43187e-05 (* 0.0454545 = 2.01448e-06 loss) | |
| I0407 15:53:12.269282 1004 solver.cpp:245] Train net output #39: loss/loss18 = 4.77141e-05 (* 0.0454545 = 2.16882e-06 loss) | |
| I0407 15:53:12.269299 1004 solver.cpp:245] Train net output #40: loss/loss19 = 4.84745e-05 (* 0.0454545 = 2.20339e-06 loss) | |
| I0407 15:53:12.269312 1004 solver.cpp:245] Train net output #41: loss/loss20 = 4.46619e-05 (* 0.0454545 = 2.03008e-06 loss) | |
| I0407 15:53:12.269326 1004 solver.cpp:245] Train net output #42: loss/loss21 = 4.73643e-05 (* 0.0454545 = 2.15292e-06 loss) | |
| I0407 15:53:12.269340 1004 solver.cpp:245] Train net output #43: loss/loss22 = 4.41923e-05 (* 0.0454545 = 2.00874e-06 loss) | |
| I0407 15:53:12.269352 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:53:12.269364 1004 solver.cpp:245] Train net output #45: total_confidence = 3.51629e-05 | |
| I0407 15:53:12.269377 1004 sgd_solver.cpp:106] Iteration 29500, lr = 0.000941 | |
| I0407 15:53:50.383518 1004 solver.cpp:338] Iteration 30000, Testing net (#0) | |
| I0407 15:53:58.329470 1004 solver.cpp:393] Test loss: 0.994279 | |
| I0407 15:53:58.329516 1004 solver.cpp:406] Test net output #0: loss/accuracy01 = 0.083 | |
| I0407 15:53:58.329533 1004 solver.cpp:406] Test net output #1: loss/accuracy02 = 0.122 | |
| I0407 15:53:58.329546 1004 solver.cpp:406] Test net output #2: loss/accuracy03 = 0.068 | |
| I0407 15:53:58.329558 1004 solver.cpp:406] Test net output #3: loss/accuracy04 = 0.086 | |
| I0407 15:53:58.329571 1004 solver.cpp:406] Test net output #4: loss/accuracy05 = 0.212 | |
| I0407 15:53:58.329582 1004 solver.cpp:406] Test net output #5: loss/accuracy06 = 0.501 | |
| I0407 15:53:58.329593 1004 solver.cpp:406] Test net output #6: loss/accuracy07 = 0.893 | |
| I0407 15:53:58.329604 1004 solver.cpp:406] Test net output #7: loss/accuracy08 = 0.97 | |
| I0407 15:53:58.329617 1004 solver.cpp:406] Test net output #8: loss/accuracy09 = 0.995 | |
| I0407 15:53:58.329628 1004 solver.cpp:406] Test net output #9: loss/accuracy10 = 0.998 | |
| I0407 15:53:58.329639 1004 solver.cpp:406] Test net output #10: loss/accuracy11 = 1 | |
| I0407 15:53:58.329651 1004 solver.cpp:406] Test net output #11: loss/accuracy12 = 1 | |
| I0407 15:53:58.329663 1004 solver.cpp:406] Test net output #12: loss/accuracy13 = 1 | |
| I0407 15:53:58.329674 1004 solver.cpp:406] Test net output #13: loss/accuracy14 = 1 | |
| I0407 15:53:58.329684 1004 solver.cpp:406] Test net output #14: loss/accuracy15 = 1 | |
| I0407 15:53:58.329695 1004 solver.cpp:406] Test net output #15: loss/accuracy16 = 1 | |
| I0407 15:53:58.329706 1004 solver.cpp:406] Test net output #16: loss/accuracy17 = 1 | |
| I0407 15:53:58.329718 1004 solver.cpp:406] Test net output #17: loss/accuracy18 = 1 | |
| I0407 15:53:58.329730 1004 solver.cpp:406] Test net output #18: loss/accuracy19 = 1 | |
| I0407 15:53:58.329741 1004 solver.cpp:406] Test net output #19: loss/accuracy20 = 1 | |
| I0407 15:53:58.329751 1004 solver.cpp:406] Test net output #20: loss/accuracy21 = 1 | |
| I0407 15:53:58.329762 1004 solver.cpp:406] Test net output #21: loss/accuracy22 = 1 | |
| I0407 15:53:58.329777 1004 solver.cpp:406] Test net output #22: loss/loss01 = 3.34025 (* 0.0454545 = 0.15183 loss) | |
| I0407 15:53:58.329792 1004 solver.cpp:406] Test net output #23: loss/loss02 = 3.55437 (* 0.0454545 = 0.161562 loss) | |
| I0407 15:53:58.329805 1004 solver.cpp:406] Test net output #24: loss/loss03 = 3.60363 (* 0.0454545 = 0.163801 loss) | |
| I0407 15:53:58.329819 1004 solver.cpp:406] Test net output #25: loss/loss04 = 3.6025 (* 0.0454545 = 0.16375 loss) | |
| I0407 15:53:58.329833 1004 solver.cpp:406] Test net output #26: loss/loss05 = 3.4951 (* 0.0454545 = 0.158868 loss) | |
| I0407 15:53:58.329846 1004 solver.cpp:406] Test net output #27: loss/loss06 = 2.59549 (* 0.0454545 = 0.117977 loss) | |
| I0407 15:53:58.329859 1004 solver.cpp:406] Test net output #28: loss/loss07 = 1.03341 (* 0.0454545 = 0.0469731 loss) | |
| I0407 15:53:58.329874 1004 solver.cpp:406] Test net output #29: loss/loss08 = 0.40305 (* 0.0454545 = 0.0183205 loss) | |
| I0407 15:53:58.329887 1004 solver.cpp:406] Test net output #30: loss/loss09 = 0.1158 (* 0.0454545 = 0.00526364 loss) | |
| I0407 15:53:58.329900 1004 solver.cpp:406] Test net output #31: loss/loss10 = 0.0637421 (* 0.0454545 = 0.00289737 loss) | |
| I0407 15:53:58.329916 1004 solver.cpp:406] Test net output #32: loss/loss11 = 0.00560316 (* 0.0454545 = 0.000254689 loss) | |
| I0407 15:53:58.329932 1004 solver.cpp:406] Test net output #33: loss/loss12 = 0.0055698 (* 0.0454545 = 0.000253173 loss) | |
| I0407 15:53:58.329946 1004 solver.cpp:406] Test net output #34: loss/loss13 = 0.00556227 (* 0.0454545 = 0.000252831 loss) | |
| I0407 15:53:58.329959 1004 solver.cpp:406] Test net output #35: loss/loss14 = 0.00557859 (* 0.0454545 = 0.000253572 loss) | |
| I0407 15:53:58.329973 1004 solver.cpp:406] Test net output #36: loss/loss15 = 0.00558409 (* 0.0454545 = 0.000253822 loss) | |
| I0407 15:53:58.329988 1004 solver.cpp:406] Test net output #37: loss/loss16 = 0.00555049 (* 0.0454545 = 0.000252295 loss) | |
| I0407 15:53:58.330000 1004 solver.cpp:406] Test net output #38: loss/loss17 = 0.00557179 (* 0.0454545 = 0.000253263 loss) | |
| I0407 15:53:58.330047 1004 solver.cpp:406] Test net output #39: loss/loss18 = 0.00555696 (* 0.0454545 = 0.000252589 loss) | |
| I0407 15:53:58.330062 1004 solver.cpp:406] Test net output #40: loss/loss19 = 0.00554077 (* 0.0454545 = 0.000251853 loss) | |
| I0407 15:53:58.330076 1004 solver.cpp:406] Test net output #41: loss/loss20 = 0.00556886 (* 0.0454545 = 0.00025313 loss) | |
| I0407 15:53:58.330090 1004 solver.cpp:406] Test net output #42: loss/loss21 = 0.00556194 (* 0.0454545 = 0.000252815 loss) | |
| I0407 15:53:58.330104 1004 solver.cpp:406] Test net output #43: loss/loss22 = 0.00556013 (* 0.0454545 = 0.000252733 loss) | |
| I0407 15:53:58.330116 1004 solver.cpp:406] Test net output #44: total_accuracy = 0 | |
| I0407 15:53:58.330128 1004 solver.cpp:406] Test net output #45: total_confidence = 5.26761e-06 | |
| I0407 15:53:58.352155 1004 solver.cpp:229] Iteration 30000, loss = 1.07189 | |
| I0407 15:53:58.352191 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.25 | |
| I0407 15:53:58.352208 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:53:58.352221 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 15:53:58.352233 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 15:53:58.352246 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 15:53:58.352257 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 15:53:58.352269 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.5625 | |
| I0407 15:53:58.352282 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 15:53:58.352294 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:53:58.352306 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:53:58.352319 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:53:58.352330 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:53:58.352341 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:53:58.352352 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:53:58.352365 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:53:58.352376 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:53:58.352387 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:53:58.352399 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:53:58.352411 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:53:58.352426 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:53:58.352437 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:53:58.352448 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:53:58.352463 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.22551 (* 0.0454545 = 0.146614 loss) | |
| I0407 15:53:58.352478 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.51585 (* 0.0454545 = 0.159811 loss) | |
| I0407 15:53:58.352491 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.57602 (* 0.0454545 = 0.162546 loss) | |
| I0407 15:53:58.352505 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.54169 (* 0.0454545 = 0.160986 loss) | |
| I0407 15:53:58.352519 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.2083 (* 0.0454545 = 0.145832 loss) | |
| I0407 15:53:58.352533 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.66217 (* 0.0454545 = 0.121008 loss) | |
| I0407 15:53:58.352546 1004 solver.cpp:245] Train net output #28: loss/loss07 = 2.19758 (* 0.0454545 = 0.09989 loss) | |
| I0407 15:53:58.352560 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.04029 (* 0.0454545 = 0.0472861 loss) | |
| I0407 15:53:58.352574 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.408326 (* 0.0454545 = 0.0185603 loss) | |
| I0407 15:53:58.352588 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0455885 (* 0.0454545 = 0.0020722 loss) | |
| I0407 15:53:58.352619 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.00170861 (* 0.0454545 = 7.76641e-05 loss) | |
| I0407 15:53:58.352635 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00172633 (* 0.0454545 = 7.84695e-05 loss) | |
| I0407 15:53:58.352650 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.00166014 (* 0.0454545 = 7.54608e-05 loss) | |
| I0407 15:53:58.352664 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00166684 (* 0.0454545 = 7.57655e-05 loss) | |
| I0407 15:53:58.352679 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.00175873 (* 0.0454545 = 7.99421e-05 loss) | |
| I0407 15:53:58.352694 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.00177878 (* 0.0454545 = 8.08534e-05 loss) | |
| I0407 15:53:58.352707 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.00165501 (* 0.0454545 = 7.52276e-05 loss) | |
| I0407 15:53:58.352721 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.00169914 (* 0.0454545 = 7.72335e-05 loss) | |
| I0407 15:53:58.352735 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00163482 (* 0.0454545 = 7.43101e-05 loss) | |
| I0407 15:53:58.352749 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.0016204 (* 0.0454545 = 7.36547e-05 loss) | |
| I0407 15:53:58.352763 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00165812 (* 0.0454545 = 7.53691e-05 loss) | |
| I0407 15:53:58.352778 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00176593 (* 0.0454545 = 8.02697e-05 loss) | |
| I0407 15:53:58.352790 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:53:58.352802 1004 solver.cpp:245] Train net output #45: total_confidence = 1.73855e-06 | |
| I0407 15:53:58.352816 1004 sgd_solver.cpp:106] Iteration 30000, lr = 0.00094 | |
| I0407 15:54:36.321979 1004 solver.cpp:229] Iteration 30500, loss = 1.08251 | |
| I0407 15:54:36.322129 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 15:54:36.322149 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:54:36.322161 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:54:36.322173 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 15:54:36.322185 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.0625 | |
| I0407 15:54:36.322199 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 15:54:36.322211 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.5625 | |
| I0407 15:54:36.322224 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 15:54:36.322237 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.875 | |
| I0407 15:54:36.322248 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 15:54:36.322260 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:54:36.322271 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:54:36.322283 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:54:36.322295 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:54:36.322306 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:54:36.322319 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:54:36.322330 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:54:36.322341 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:54:36.322353 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:54:36.322365 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:54:36.322376 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:54:36.322387 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:54:36.322403 1004 solver.cpp:245] Train net output #22: loss/loss01 = 4.00713 (* 0.0454545 = 0.182142 loss) | |
| I0407 15:54:36.322417 1004 solver.cpp:245] Train net output #23: loss/loss02 = 4.00183 (* 0.0454545 = 0.181901 loss) | |
| I0407 15:54:36.322432 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.98707 (* 0.0454545 = 0.181231 loss) | |
| I0407 15:54:36.322445 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.92972 (* 0.0454545 = 0.178623 loss) | |
| I0407 15:54:36.322459 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.87582 (* 0.0454545 = 0.176174 loss) | |
| I0407 15:54:36.322474 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.18558 (* 0.0454545 = 0.144799 loss) | |
| I0407 15:54:36.322487 1004 solver.cpp:245] Train net output #28: loss/loss07 = 2.61361 (* 0.0454545 = 0.118801 loss) | |
| I0407 15:54:36.322501 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.750627 (* 0.0454545 = 0.0341194 loss) | |
| I0407 15:54:36.322515 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.714739 (* 0.0454545 = 0.0324881 loss) | |
| I0407 15:54:36.322530 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.376059 (* 0.0454545 = 0.0170936 loss) | |
| I0407 15:54:36.322543 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.00106519 (* 0.0454545 = 4.84175e-05 loss) | |
| I0407 15:54:36.322557 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00104049 (* 0.0454545 = 4.72951e-05 loss) | |
| I0407 15:54:36.322572 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.00102134 (* 0.0454545 = 4.64244e-05 loss) | |
| I0407 15:54:36.322587 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00102372 (* 0.0454545 = 4.65326e-05 loss) | |
| I0407 15:54:36.322600 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.00105694 (* 0.0454545 = 4.80429e-05 loss) | |
| I0407 15:54:36.322614 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.00105928 (* 0.0454545 = 4.8149e-05 loss) | |
| I0407 15:54:36.322628 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.00109846 (* 0.0454545 = 4.99301e-05 loss) | |
| I0407 15:54:36.322656 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.00109195 (* 0.0454545 = 4.96342e-05 loss) | |
| I0407 15:54:36.322671 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00103023 (* 0.0454545 = 4.68284e-05 loss) | |
| I0407 15:54:36.322686 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.00103263 (* 0.0454545 = 4.69378e-05 loss) | |
| I0407 15:54:36.322700 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00107275 (* 0.0454545 = 4.87614e-05 loss) | |
| I0407 15:54:36.322715 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00108264 (* 0.0454545 = 4.92111e-05 loss) | |
| I0407 15:54:36.322739 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:54:36.322752 1004 solver.cpp:245] Train net output #45: total_confidence = 5.96634e-07 | |
| I0407 15:54:36.322767 1004 sgd_solver.cpp:106] Iteration 30500, lr = 0.000939 | |
| I0407 15:55:14.930878 1004 solver.cpp:229] Iteration 31000, loss = 1.0714 | |
| I0407 15:55:14.931049 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:55:14.931069 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:55:14.931085 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 15:55:14.931097 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 15:55:14.931109 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.5 | |
| I0407 15:55:14.931123 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5625 | |
| I0407 15:55:14.931134 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 15:55:14.931145 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 15:55:14.931157 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:55:14.931169 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:55:14.931180 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:55:14.931192 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:55:14.931203 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:55:14.931216 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:55:14.931226 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:55:14.931238 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:55:14.931249 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:55:14.931262 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:55:14.931272 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:55:14.931284 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:55:14.931295 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:55:14.931308 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:55:14.931340 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.12228 (* 0.0454545 = 0.141922 loss) | |
| I0407 15:55:14.931356 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.45282 (* 0.0454545 = 0.156946 loss) | |
| I0407 15:55:14.931371 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.54739 (* 0.0454545 = 0.161245 loss) | |
| I0407 15:55:14.931385 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.42582 (* 0.0454545 = 0.155719 loss) | |
| I0407 15:55:14.931399 1004 solver.cpp:245] Train net output #26: loss/loss05 = 2.54768 (* 0.0454545 = 0.115804 loss) | |
| I0407 15:55:14.931413 1004 solver.cpp:245] Train net output #27: loss/loss06 = 1.97001 (* 0.0454545 = 0.089546 loss) | |
| I0407 15:55:14.931427 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.959494 (* 0.0454545 = 0.0436134 loss) | |
| I0407 15:55:14.931442 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.0963315 (* 0.0454545 = 0.0043787 loss) | |
| I0407 15:55:14.931457 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0317472 (* 0.0454545 = 0.00144305 loss) | |
| I0407 15:55:14.931470 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0132458 (* 0.0454545 = 0.00060208 loss) | |
| I0407 15:55:14.931484 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000261163 (* 0.0454545 = 1.18711e-05 loss) | |
| I0407 15:55:14.931499 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000255931 (* 0.0454545 = 1.16332e-05 loss) | |
| I0407 15:55:14.931514 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000258018 (* 0.0454545 = 1.17281e-05 loss) | |
| I0407 15:55:14.931527 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000237045 (* 0.0454545 = 1.07748e-05 loss) | |
| I0407 15:55:14.931541 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000258377 (* 0.0454545 = 1.17444e-05 loss) | |
| I0407 15:55:14.931555 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000260707 (* 0.0454545 = 1.18503e-05 loss) | |
| I0407 15:55:14.931571 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000257758 (* 0.0454545 = 1.17163e-05 loss) | |
| I0407 15:55:14.931602 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000249825 (* 0.0454545 = 1.13557e-05 loss) | |
| I0407 15:55:14.931617 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000240177 (* 0.0454545 = 1.09171e-05 loss) | |
| I0407 15:55:14.931632 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000254811 (* 0.0454545 = 1.15823e-05 loss) | |
| I0407 15:55:14.931645 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00025305 (* 0.0454545 = 1.15023e-05 loss) | |
| I0407 15:55:14.931659 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000250898 (* 0.0454545 = 1.14044e-05 loss) | |
| I0407 15:55:14.931671 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:55:14.931684 1004 solver.cpp:245] Train net output #45: total_confidence = 6.49183e-06 | |
| I0407 15:55:14.931696 1004 sgd_solver.cpp:106] Iteration 31000, lr = 0.000938 | |
| I0407 15:55:53.399649 1004 solver.cpp:229] Iteration 31500, loss = 1.07585 | |
| I0407 15:55:53.399786 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:55:53.399806 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:55:53.399819 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:55:53.399832 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 15:55:53.399843 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 15:55:53.399855 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 15:55:53.399868 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 15:55:53.399879 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 15:55:53.399891 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:55:53.399904 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:55:53.399915 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:55:53.399930 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:55:53.399941 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:55:53.399953 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:55:53.399966 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:55:53.399976 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:55:53.399988 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:55:53.400001 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:55:53.400012 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:55:53.400023 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:55:53.400034 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:55:53.400046 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:55:53.400061 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.67071 (* 0.0454545 = 0.16685 loss) | |
| I0407 15:55:53.400076 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.68787 (* 0.0454545 = 0.167631 loss) | |
| I0407 15:55:53.400090 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.6813 (* 0.0454545 = 0.167332 loss) | |
| I0407 15:55:53.400104 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.59748 (* 0.0454545 = 0.163522 loss) | |
| I0407 15:55:53.400117 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.4063 (* 0.0454545 = 0.154832 loss) | |
| I0407 15:55:53.400131 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.15997 (* 0.0454545 = 0.143635 loss) | |
| I0407 15:55:53.400146 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.41375 (* 0.0454545 = 0.0642612 loss) | |
| I0407 15:55:53.400159 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.826993 (* 0.0454545 = 0.0375906 loss) | |
| I0407 15:55:53.400173 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.45899 (* 0.0454545 = 0.0208632 loss) | |
| I0407 15:55:53.400187 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.00135484 (* 0.0454545 = 6.15836e-05 loss) | |
| I0407 15:55:53.400202 1004 solver.cpp:245] Train net output #32: loss/loss11 = 1.36346e-06 (* 0.0454545 = 6.19754e-08 loss) | |
| I0407 15:55:53.400216 1004 solver.cpp:245] Train net output #33: loss/loss12 = 1.34856e-06 (* 0.0454545 = 6.12981e-08 loss) | |
| I0407 15:55:53.400230 1004 solver.cpp:245] Train net output #34: loss/loss13 = 1.37836e-06 (* 0.0454545 = 6.26528e-08 loss) | |
| I0407 15:55:53.400244 1004 solver.cpp:245] Train net output #35: loss/loss14 = 1.25915e-06 (* 0.0454545 = 5.72341e-08 loss) | |
| I0407 15:55:53.400259 1004 solver.cpp:245] Train net output #36: loss/loss15 = 1.33366e-06 (* 0.0454545 = 6.06208e-08 loss) | |
| I0407 15:55:53.400272 1004 solver.cpp:245] Train net output #37: loss/loss16 = 1.2219e-06 (* 0.0454545 = 5.55408e-08 loss) | |
| I0407 15:55:53.400286 1004 solver.cpp:245] Train net output #38: loss/loss17 = 1.32621e-06 (* 0.0454545 = 6.02821e-08 loss) | |
| I0407 15:55:53.400318 1004 solver.cpp:245] Train net output #39: loss/loss18 = 1.32621e-06 (* 0.0454545 = 6.02821e-08 loss) | |
| I0407 15:55:53.400333 1004 solver.cpp:245] Train net output #40: loss/loss19 = 1.18465e-06 (* 0.0454545 = 5.38475e-08 loss) | |
| I0407 15:55:53.400347 1004 solver.cpp:245] Train net output #41: loss/loss20 = 1.24425e-06 (* 0.0454545 = 5.65568e-08 loss) | |
| I0407 15:55:53.400362 1004 solver.cpp:245] Train net output #42: loss/loss21 = 1.21445e-06 (* 0.0454545 = 5.52022e-08 loss) | |
| I0407 15:55:53.400375 1004 solver.cpp:245] Train net output #43: loss/loss22 = 1.31131e-06 (* 0.0454545 = 5.96048e-08 loss) | |
| I0407 15:55:53.400388 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:55:53.400399 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000427293 | |
| I0407 15:55:53.400413 1004 sgd_solver.cpp:106] Iteration 31500, lr = 0.000937 | |
| I0407 15:56:31.685160 1004 solver.cpp:229] Iteration 32000, loss = 1.07593 | |
| I0407 15:56:31.685302 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.1875 | |
| I0407 15:56:31.685322 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:56:31.685335 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 15:56:31.685348 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 15:56:31.685360 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 15:56:31.685372 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 15:56:31.685385 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 15:56:31.685397 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 15:56:31.685410 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:56:31.685421 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 15:56:31.685433 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:56:31.685444 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:56:31.685456 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:56:31.685468 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:56:31.685479 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:56:31.685492 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:56:31.685503 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:56:31.685515 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:56:31.685526 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:56:31.685539 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:56:31.685550 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:56:31.685562 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:56:31.685577 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.71415 (* 0.0454545 = 0.168825 loss) | |
| I0407 15:56:31.685592 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.91644 (* 0.0454545 = 0.17802 loss) | |
| I0407 15:56:31.685606 1004 solver.cpp:245] Train net output #24: loss/loss03 = 4.00272 (* 0.0454545 = 0.181942 loss) | |
| I0407 15:56:31.685621 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.81215 (* 0.0454545 = 0.173279 loss) | |
| I0407 15:56:31.685634 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.44191 (* 0.0454545 = 0.15645 loss) | |
| I0407 15:56:31.685648 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.72917 (* 0.0454545 = 0.124053 loss) | |
| I0407 15:56:31.685662 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.27248 (* 0.0454545 = 0.0578401 loss) | |
| I0407 15:56:31.685677 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.07812 (* 0.0454545 = 0.0490054 loss) | |
| I0407 15:56:31.685691 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.380127 (* 0.0454545 = 0.0172785 loss) | |
| I0407 15:56:31.685706 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.367777 (* 0.0454545 = 0.0167171 loss) | |
| I0407 15:56:31.685720 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000483402 (* 0.0454545 = 2.19728e-05 loss) | |
| I0407 15:56:31.685735 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000507275 (* 0.0454545 = 2.3058e-05 loss) | |
| I0407 15:56:31.685750 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000487998 (* 0.0454545 = 2.21817e-05 loss) | |
| I0407 15:56:31.685763 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000531118 (* 0.0454545 = 2.41417e-05 loss) | |
| I0407 15:56:31.685778 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000502196 (* 0.0454545 = 2.28271e-05 loss) | |
| I0407 15:56:31.685792 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000505707 (* 0.0454545 = 2.29867e-05 loss) | |
| I0407 15:56:31.685806 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000525503 (* 0.0454545 = 2.38865e-05 loss) | |
| I0407 15:56:31.685834 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000527925 (* 0.0454545 = 2.39966e-05 loss) | |
| I0407 15:56:31.685849 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000497244 (* 0.0454545 = 2.2602e-05 loss) | |
| I0407 15:56:31.685863 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000490866 (* 0.0454545 = 2.23121e-05 loss) | |
| I0407 15:56:31.685878 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000533428 (* 0.0454545 = 2.42467e-05 loss) | |
| I0407 15:56:31.685891 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000538928 (* 0.0454545 = 2.44967e-05 loss) | |
| I0407 15:56:31.685904 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:56:31.685920 1004 solver.cpp:245] Train net output #45: total_confidence = 6.23467e-05 | |
| I0407 15:56:31.685936 1004 sgd_solver.cpp:106] Iteration 32000, lr = 0.000936 | |
| I0407 15:57:09.868158 1004 solver.cpp:229] Iteration 32500, loss = 1.07422 | |
| I0407 15:57:09.868278 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 15:57:09.868297 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:57:09.868310 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 15:57:09.868324 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 15:57:09.868336 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 15:57:09.868350 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5 | |
| I0407 15:57:09.868361 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 15:57:09.868373 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 15:57:09.868386 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:57:09.868397 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:57:09.868408 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:57:09.868420 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:57:09.868432 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:57:09.868443 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:57:09.868455 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:57:09.868468 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:57:09.868479 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:57:09.868491 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:57:09.868502 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:57:09.868515 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:57:09.868525 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:57:09.868537 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:57:09.868553 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.35797 (* 0.0454545 = 0.152635 loss) | |
| I0407 15:57:09.868568 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.40078 (* 0.0454545 = 0.154581 loss) | |
| I0407 15:57:09.868582 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.52943 (* 0.0454545 = 0.160428 loss) | |
| I0407 15:57:09.868597 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.38513 (* 0.0454545 = 0.15387 loss) | |
| I0407 15:57:09.868612 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.13473 (* 0.0454545 = 0.142488 loss) | |
| I0407 15:57:09.868625 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.06923 (* 0.0454545 = 0.0940559 loss) | |
| I0407 15:57:09.868638 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.63105 (* 0.0454545 = 0.0741387 loss) | |
| I0407 15:57:09.868652 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.334254 (* 0.0454545 = 0.0151934 loss) | |
| I0407 15:57:09.868667 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0181232 (* 0.0454545 = 0.000823784 loss) | |
| I0407 15:57:09.868681 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.00534685 (* 0.0454545 = 0.000243039 loss) | |
| I0407 15:57:09.868696 1004 solver.cpp:245] Train net output #32: loss/loss11 = 1.67271e-05 (* 0.0454545 = 7.60322e-07 loss) | |
| I0407 15:57:09.868710 1004 solver.cpp:245] Train net output #33: loss/loss12 = 1.67271e-05 (* 0.0454545 = 7.60322e-07 loss) | |
| I0407 15:57:09.868724 1004 solver.cpp:245] Train net output #34: loss/loss13 = 1.70028e-05 (* 0.0454545 = 7.72853e-07 loss) | |
| I0407 15:57:09.868738 1004 solver.cpp:245] Train net output #35: loss/loss14 = 1.55796e-05 (* 0.0454545 = 7.08164e-07 loss) | |
| I0407 15:57:09.868752 1004 solver.cpp:245] Train net output #36: loss/loss15 = 1.67941e-05 (* 0.0454545 = 7.6337e-07 loss) | |
| I0407 15:57:09.868767 1004 solver.cpp:245] Train net output #37: loss/loss16 = 1.61459e-05 (* 0.0454545 = 7.33905e-07 loss) | |
| I0407 15:57:09.868782 1004 solver.cpp:245] Train net output #38: loss/loss17 = 1.64141e-05 (* 0.0454545 = 7.46097e-07 loss) | |
| I0407 15:57:09.868813 1004 solver.cpp:245] Train net output #39: loss/loss18 = 1.58404e-05 (* 0.0454545 = 7.20019e-07 loss) | |
| I0407 15:57:09.868829 1004 solver.cpp:245] Train net output #40: loss/loss19 = 1.62875e-05 (* 0.0454545 = 7.40339e-07 loss) | |
| I0407 15:57:09.868842 1004 solver.cpp:245] Train net output #41: loss/loss20 = 1.80013e-05 (* 0.0454545 = 8.18239e-07 loss) | |
| I0407 15:57:09.868856 1004 solver.cpp:245] Train net output #42: loss/loss21 = 1.61981e-05 (* 0.0454545 = 7.36276e-07 loss) | |
| I0407 15:57:09.868870 1004 solver.cpp:245] Train net output #43: loss/loss22 = 1.68835e-05 (* 0.0454545 = 7.67434e-07 loss) | |
| I0407 15:57:09.868882 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:57:09.868894 1004 solver.cpp:245] Train net output #45: total_confidence = 7.90301e-05 | |
| I0407 15:57:09.868907 1004 sgd_solver.cpp:106] Iteration 32500, lr = 0.000935 | |
| I0407 15:57:48.126260 1004 solver.cpp:229] Iteration 33000, loss = 1.06462 | |
| I0407 15:57:48.126366 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 15:57:48.126387 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:57:48.126411 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:57:48.126435 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 15:57:48.126449 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 15:57:48.126462 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 15:57:48.126476 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 15:57:48.126487 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 15:57:48.126498 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:57:48.126510 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:57:48.126521 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:57:48.126533 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:57:48.126544 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:57:48.126555 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:57:48.126567 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:57:48.126579 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:57:48.126590 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:57:48.126601 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:57:48.126613 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:57:48.126624 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:57:48.126636 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:57:48.126647 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:57:48.126662 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.5795 (* 0.0454545 = 0.162704 loss) | |
| I0407 15:57:48.126677 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.9684 (* 0.0454545 = 0.180382 loss) | |
| I0407 15:57:48.126691 1004 solver.cpp:245] Train net output #24: loss/loss03 = 4.00917 (* 0.0454545 = 0.182235 loss) | |
| I0407 15:57:48.126705 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.83143 (* 0.0454545 = 0.174156 loss) | |
| I0407 15:57:48.126719 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.97016 (* 0.0454545 = 0.180462 loss) | |
| I0407 15:57:48.126734 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.07964 (* 0.0454545 = 0.139984 loss) | |
| I0407 15:57:48.126746 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.72879 (* 0.0454545 = 0.0785812 loss) | |
| I0407 15:57:48.126761 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.100331 (* 0.0454545 = 0.00456048 loss) | |
| I0407 15:57:48.126775 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.036329 (* 0.0454545 = 0.00165132 loss) | |
| I0407 15:57:48.126791 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0140389 (* 0.0454545 = 0.000638131 loss) | |
| I0407 15:57:48.126804 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000156272 (* 0.0454545 = 7.10329e-06 loss) | |
| I0407 15:57:48.126818 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000165019 (* 0.0454545 = 7.50086e-06 loss) | |
| I0407 15:57:48.126832 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000156404 (* 0.0454545 = 7.10927e-06 loss) | |
| I0407 15:57:48.126847 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000148324 (* 0.0454545 = 6.74199e-06 loss) | |
| I0407 15:57:48.126862 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000151868 (* 0.0454545 = 6.90311e-06 loss) | |
| I0407 15:57:48.126875 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000155407 (* 0.0454545 = 7.06397e-06 loss) | |
| I0407 15:57:48.126889 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000151685 (* 0.0454545 = 6.89479e-06 loss) | |
| I0407 15:57:48.126924 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000155654 (* 0.0454545 = 7.07518e-06 loss) | |
| I0407 15:57:48.126940 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000149166 (* 0.0454545 = 6.78029e-06 loss) | |
| I0407 15:57:48.126955 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.00016041 (* 0.0454545 = 7.29138e-06 loss) | |
| I0407 15:57:48.126968 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000154868 (* 0.0454545 = 7.03947e-06 loss) | |
| I0407 15:57:48.126982 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000143431 (* 0.0454545 = 6.51957e-06 loss) | |
| I0407 15:57:48.126994 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:57:48.127005 1004 solver.cpp:245] Train net output #45: total_confidence = 1.42146e-06 | |
| I0407 15:57:48.127018 1004 sgd_solver.cpp:106] Iteration 33000, lr = 0.000934 | |
| I0407 15:58:27.031088 1004 solver.cpp:229] Iteration 33500, loss = 1.07802 | |
| I0407 15:58:27.031208 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 15:58:27.031225 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 15:58:27.031237 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:58:27.031250 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 15:58:27.031260 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.0625 | |
| I0407 15:58:27.031273 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.1875 | |
| I0407 15:58:27.031286 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.5625 | |
| I0407 15:58:27.031297 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 15:58:27.031308 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:58:27.031321 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:58:27.031332 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:58:27.031358 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:58:27.031370 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:58:27.031381 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:58:27.031394 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:58:27.031404 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:58:27.031416 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:58:27.031427 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:58:27.031440 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:58:27.031450 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:58:27.031462 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:58:27.031473 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:58:27.031489 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.66791 (* 0.0454545 = 0.166723 loss) | |
| I0407 15:58:27.031503 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.66495 (* 0.0454545 = 0.166589 loss) | |
| I0407 15:58:27.031517 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.79055 (* 0.0454545 = 0.172298 loss) | |
| I0407 15:58:27.031532 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.69751 (* 0.0454545 = 0.168069 loss) | |
| I0407 15:58:27.031544 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.74404 (* 0.0454545 = 0.170184 loss) | |
| I0407 15:58:27.031558 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.44804 (* 0.0454545 = 0.156729 loss) | |
| I0407 15:58:27.031572 1004 solver.cpp:245] Train net output #28: loss/loss07 = 2.29003 (* 0.0454545 = 0.104092 loss) | |
| I0407 15:58:27.031586 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.479252 (* 0.0454545 = 0.0217842 loss) | |
| I0407 15:58:27.031600 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.101969 (* 0.0454545 = 0.00463494 loss) | |
| I0407 15:58:27.031615 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0510948 (* 0.0454545 = 0.00232249 loss) | |
| I0407 15:58:27.031628 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.00176135 (* 0.0454545 = 8.00613e-05 loss) | |
| I0407 15:58:27.031642 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00170982 (* 0.0454545 = 7.77189e-05 loss) | |
| I0407 15:58:27.031657 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.00159607 (* 0.0454545 = 7.25484e-05 loss) | |
| I0407 15:58:27.031672 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00162965 (* 0.0454545 = 7.40751e-05 loss) | |
| I0407 15:58:27.031685 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.00165447 (* 0.0454545 = 7.52034e-05 loss) | |
| I0407 15:58:27.031699 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.0016273 (* 0.0454545 = 7.39682e-05 loss) | |
| I0407 15:58:27.031713 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.00161839 (* 0.0454545 = 7.35631e-05 loss) | |
| I0407 15:58:27.031975 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.00160402 (* 0.0454545 = 7.29102e-05 loss) | |
| I0407 15:58:27.031991 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00150534 (* 0.0454545 = 6.84246e-05 loss) | |
| I0407 15:58:27.032006 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.00160292 (* 0.0454545 = 7.28598e-05 loss) | |
| I0407 15:58:27.032019 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00160107 (* 0.0454545 = 7.27757e-05 loss) | |
| I0407 15:58:27.032033 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00162796 (* 0.0454545 = 7.3998e-05 loss) | |
| I0407 15:58:27.032045 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:58:27.032058 1004 solver.cpp:245] Train net output #45: total_confidence = 7.10858e-06 | |
| I0407 15:58:27.032070 1004 sgd_solver.cpp:106] Iteration 33500, lr = 0.000933 | |
| I0407 15:59:05.386404 1004 solver.cpp:229] Iteration 34000, loss = 1.0703 | |
| I0407 15:59:05.386575 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 15:59:05.386595 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.125 | |
| I0407 15:59:05.386610 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 15:59:05.386621 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 15:59:05.386633 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 15:59:05.386646 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 15:59:05.386658 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.625 | |
| I0407 15:59:05.386669 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 15:59:05.386682 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 15:59:05.386693 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 15:59:05.386705 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:59:05.386716 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:59:05.386729 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:59:05.386739 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:59:05.386751 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:59:05.386762 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:59:05.386775 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:59:05.386786 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:59:05.386797 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:59:05.386808 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:59:05.386821 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:59:05.386832 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:59:05.386847 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.50474 (* 0.0454545 = 0.159307 loss) | |
| I0407 15:59:05.386862 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.66708 (* 0.0454545 = 0.166685 loss) | |
| I0407 15:59:05.386876 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.70671 (* 0.0454545 = 0.168487 loss) | |
| I0407 15:59:05.386889 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.77804 (* 0.0454545 = 0.171729 loss) | |
| I0407 15:59:05.386904 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.37317 (* 0.0454545 = 0.153326 loss) | |
| I0407 15:59:05.386919 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.06722 (* 0.0454545 = 0.139419 loss) | |
| I0407 15:59:05.386934 1004 solver.cpp:245] Train net output #28: loss/loss07 = 2.11784 (* 0.0454545 = 0.0962653 loss) | |
| I0407 15:59:05.386948 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.877739 (* 0.0454545 = 0.0398972 loss) | |
| I0407 15:59:05.386962 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.417094 (* 0.0454545 = 0.0189588 loss) | |
| I0407 15:59:05.386976 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.439281 (* 0.0454545 = 0.0199673 loss) | |
| I0407 15:59:05.386991 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000193973 (* 0.0454545 = 8.81696e-06 loss) | |
| I0407 15:59:05.387004 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000163731 (* 0.0454545 = 7.44233e-06 loss) | |
| I0407 15:59:05.387018 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000188717 (* 0.0454545 = 8.57805e-06 loss) | |
| I0407 15:59:05.387032 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000183507 (* 0.0454545 = 8.34124e-06 loss) | |
| I0407 15:59:05.387048 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000179931 (* 0.0454545 = 8.17866e-06 loss) | |
| I0407 15:59:05.387061 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000153314 (* 0.0454545 = 6.96881e-06 loss) | |
| I0407 15:59:05.387079 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000166869 (* 0.0454545 = 7.58497e-06 loss) | |
| I0407 15:59:05.387106 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.00016571 (* 0.0454545 = 7.53228e-06 loss) | |
| I0407 15:59:05.387122 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000162508 (* 0.0454545 = 7.38671e-06 loss) | |
| I0407 15:59:05.387136 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000146992 (* 0.0454545 = 6.68146e-06 loss) | |
| I0407 15:59:05.387151 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000156281 (* 0.0454545 = 7.1037e-06 loss) | |
| I0407 15:59:05.387164 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000165958 (* 0.0454545 = 7.54353e-06 loss) | |
| I0407 15:59:05.387176 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:59:05.387188 1004 solver.cpp:245] Train net output #45: total_confidence = 2.8937e-05 | |
| I0407 15:59:05.387202 1004 sgd_solver.cpp:106] Iteration 34000, lr = 0.000932 | |
| I0407 15:59:43.878914 1004 solver.cpp:229] Iteration 34500, loss = 1.06259 | |
| I0407 15:59:43.879067 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 15:59:43.879088 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 15:59:43.879102 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 15:59:43.879114 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 15:59:43.879127 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.0625 | |
| I0407 15:59:43.879138 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 15:59:43.879150 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 15:59:43.879163 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 15:59:43.879174 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 15:59:43.879186 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 15:59:43.879197 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 15:59:43.879209 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 15:59:43.879220 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 15:59:43.879231 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 15:59:43.879243 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 15:59:43.879254 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 15:59:43.879266 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 15:59:43.879277 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 15:59:43.879288 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 15:59:43.879299 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 15:59:43.879312 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 15:59:43.879343 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 15:59:43.879361 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.6249 (* 0.0454545 = 0.164768 loss) | |
| I0407 15:59:43.879376 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.6807 (* 0.0454545 = 0.167305 loss) | |
| I0407 15:59:43.879390 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.57676 (* 0.0454545 = 0.16258 loss) | |
| I0407 15:59:43.879405 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.6113 (* 0.0454545 = 0.16415 loss) | |
| I0407 15:59:43.879417 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.79806 (* 0.0454545 = 0.172639 loss) | |
| I0407 15:59:43.879431 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.48654 (* 0.0454545 = 0.113025 loss) | |
| I0407 15:59:43.879446 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.05969 (* 0.0454545 = 0.0481679 loss) | |
| I0407 15:59:43.879459 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.17528 (* 0.0454545 = 0.0534217 loss) | |
| I0407 15:59:43.879473 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0354374 (* 0.0454545 = 0.00161079 loss) | |
| I0407 15:59:43.879487 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.013778 (* 0.0454545 = 0.000626272 loss) | |
| I0407 15:59:43.879501 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000149635 (* 0.0454545 = 6.80158e-06 loss) | |
| I0407 15:59:43.879515 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000144287 (* 0.0454545 = 6.55852e-06 loss) | |
| I0407 15:59:43.879529 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000142489 (* 0.0454545 = 6.47677e-06 loss) | |
| I0407 15:59:43.879544 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000145672 (* 0.0454545 = 6.62146e-06 loss) | |
| I0407 15:59:43.879557 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000148105 (* 0.0454545 = 6.73204e-06 loss) | |
| I0407 15:59:43.879572 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000133622 (* 0.0454545 = 6.07371e-06 loss) | |
| I0407 15:59:43.879586 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000144 (* 0.0454545 = 6.54548e-06 loss) | |
| I0407 15:59:43.879618 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000148306 (* 0.0454545 = 6.74118e-06 loss) | |
| I0407 15:59:43.879634 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000141236 (* 0.0454545 = 6.41982e-06 loss) | |
| I0407 15:59:43.879647 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000143889 (* 0.0454545 = 6.54041e-06 loss) | |
| I0407 15:59:43.879662 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00014324 (* 0.0454545 = 6.51091e-06 loss) | |
| I0407 15:59:43.879675 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000153955 (* 0.0454545 = 6.99795e-06 loss) | |
| I0407 15:59:43.879688 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 15:59:43.879699 1004 solver.cpp:245] Train net output #45: total_confidence = 7.19492e-06 | |
| I0407 15:59:43.879712 1004 sgd_solver.cpp:106] Iteration 34500, lr = 0.000931 | |
| I0407 16:00:22.789160 1004 solver.cpp:338] Iteration 35000, Testing net (#0) | |
| I0407 16:00:30.796301 1004 solver.cpp:393] Test loss: 0.95736 | |
| I0407 16:00:30.796352 1004 solver.cpp:406] Test net output #0: loss/accuracy01 = 0.098 | |
| I0407 16:00:30.796370 1004 solver.cpp:406] Test net output #1: loss/accuracy02 = 0.061 | |
| I0407 16:00:30.796382 1004 solver.cpp:406] Test net output #2: loss/accuracy03 = 0.068 | |
| I0407 16:00:30.796393 1004 solver.cpp:406] Test net output #3: loss/accuracy04 = 0.09 | |
| I0407 16:00:30.796406 1004 solver.cpp:406] Test net output #4: loss/accuracy05 = 0.212 | |
| I0407 16:00:30.796417 1004 solver.cpp:406] Test net output #5: loss/accuracy06 = 0.501 | |
| I0407 16:00:30.796429 1004 solver.cpp:406] Test net output #6: loss/accuracy07 = 0.894 | |
| I0407 16:00:30.796440 1004 solver.cpp:406] Test net output #7: loss/accuracy08 = 0.97 | |
| I0407 16:00:30.796452 1004 solver.cpp:406] Test net output #8: loss/accuracy09 = 0.995 | |
| I0407 16:00:30.796463 1004 solver.cpp:406] Test net output #9: loss/accuracy10 = 0.998 | |
| I0407 16:00:30.796475 1004 solver.cpp:406] Test net output #10: loss/accuracy11 = 1 | |
| I0407 16:00:30.796486 1004 solver.cpp:406] Test net output #11: loss/accuracy12 = 1 | |
| I0407 16:00:30.796497 1004 solver.cpp:406] Test net output #12: loss/accuracy13 = 1 | |
| I0407 16:00:30.796509 1004 solver.cpp:406] Test net output #13: loss/accuracy14 = 1 | |
| I0407 16:00:30.796519 1004 solver.cpp:406] Test net output #14: loss/accuracy15 = 1 | |
| I0407 16:00:30.796530 1004 solver.cpp:406] Test net output #15: loss/accuracy16 = 1 | |
| I0407 16:00:30.796541 1004 solver.cpp:406] Test net output #16: loss/accuracy17 = 1 | |
| I0407 16:00:30.796552 1004 solver.cpp:406] Test net output #17: loss/accuracy18 = 1 | |
| I0407 16:00:30.796563 1004 solver.cpp:406] Test net output #18: loss/accuracy19 = 1 | |
| I0407 16:00:30.796574 1004 solver.cpp:406] Test net output #19: loss/accuracy20 = 1 | |
| I0407 16:00:30.796586 1004 solver.cpp:406] Test net output #20: loss/accuracy21 = 1 | |
| I0407 16:00:30.796597 1004 solver.cpp:406] Test net output #21: loss/accuracy22 = 1 | |
| I0407 16:00:30.796610 1004 solver.cpp:406] Test net output #22: loss/loss01 = 3.21739 (* 0.0454545 = 0.146245 loss) | |
| I0407 16:00:30.796624 1004 solver.cpp:406] Test net output #23: loss/loss02 = 3.49017 (* 0.0454545 = 0.158644 loss) | |
| I0407 16:00:30.796638 1004 solver.cpp:406] Test net output #24: loss/loss03 = 3.56637 (* 0.0454545 = 0.162108 loss) | |
| I0407 16:00:30.796653 1004 solver.cpp:406] Test net output #25: loss/loss04 = 3.53138 (* 0.0454545 = 0.160517 loss) | |
| I0407 16:00:30.796665 1004 solver.cpp:406] Test net output #26: loss/loss05 = 3.45855 (* 0.0454545 = 0.157207 loss) | |
| I0407 16:00:30.796679 1004 solver.cpp:406] Test net output #27: loss/loss06 = 2.48328 (* 0.0454545 = 0.112876 loss) | |
| I0407 16:00:30.796694 1004 solver.cpp:406] Test net output #28: loss/loss07 = 0.883549 (* 0.0454545 = 0.0401613 loss) | |
| I0407 16:00:30.796707 1004 solver.cpp:406] Test net output #29: loss/loss08 = 0.321354 (* 0.0454545 = 0.014607 loss) | |
| I0407 16:00:30.796720 1004 solver.cpp:406] Test net output #30: loss/loss09 = 0.069154 (* 0.0454545 = 0.00314336 loss) | |
| I0407 16:00:30.796735 1004 solver.cpp:406] Test net output #31: loss/loss10 = 0.0323339 (* 0.0454545 = 0.00146972 loss) | |
| I0407 16:00:30.796748 1004 solver.cpp:406] Test net output #32: loss/loss11 = 0.00071833 (* 0.0454545 = 3.26514e-05 loss) | |
| I0407 16:00:30.796762 1004 solver.cpp:406] Test net output #33: loss/loss12 = 0.000706482 (* 0.0454545 = 3.21128e-05 loss) | |
| I0407 16:00:30.796777 1004 solver.cpp:406] Test net output #34: loss/loss13 = 0.000701346 (* 0.0454545 = 3.18794e-05 loss) | |
| I0407 16:00:30.796790 1004 solver.cpp:406] Test net output #35: loss/loss14 = 0.000703998 (* 0.0454545 = 3.19999e-05 loss) | |
| I0407 16:00:30.796803 1004 solver.cpp:406] Test net output #36: loss/loss15 = 0.000710559 (* 0.0454545 = 3.22982e-05 loss) | |
| I0407 16:00:30.796818 1004 solver.cpp:406] Test net output #37: loss/loss16 = 0.00069334 (* 0.0454545 = 3.15155e-05 loss) | |
| I0407 16:00:30.796831 1004 solver.cpp:406] Test net output #38: loss/loss17 = 0.000698 (* 0.0454545 = 3.17273e-05 loss) | |
| I0407 16:00:30.796880 1004 solver.cpp:406] Test net output #39: loss/loss18 = 0.00070041 (* 0.0454545 = 3.18368e-05 loss) | |
| I0407 16:00:30.796896 1004 solver.cpp:406] Test net output #40: loss/loss19 = 0.000686329 (* 0.0454545 = 3.11968e-05 loss) | |
| I0407 16:00:30.796911 1004 solver.cpp:406] Test net output #41: loss/loss20 = 0.000695966 (* 0.0454545 = 3.16348e-05 loss) | |
| I0407 16:00:30.796927 1004 solver.cpp:406] Test net output #42: loss/loss21 = 0.000698768 (* 0.0454545 = 3.17622e-05 loss) | |
| I0407 16:00:30.796941 1004 solver.cpp:406] Test net output #43: loss/loss22 = 0.000700695 (* 0.0454545 = 3.18498e-05 loss) | |
| I0407 16:00:30.796953 1004 solver.cpp:406] Test net output #44: total_accuracy = 0 | |
| I0407 16:00:30.796964 1004 solver.cpp:406] Test net output #45: total_confidence = 3.80663e-05 | |
| I0407 16:00:30.819453 1004 solver.cpp:229] Iteration 35000, loss = 1.07644 | |
| I0407 16:00:30.819489 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.25 | |
| I0407 16:00:30.819504 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:00:30.819517 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 16:00:30.819530 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 16:00:30.819541 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 16:00:30.819553 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5 | |
| I0407 16:00:30.819564 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.875 | |
| I0407 16:00:30.819576 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 16:00:30.819588 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:00:30.819600 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:00:30.819612 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:00:30.819622 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:00:30.819633 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:00:30.819645 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:00:30.819656 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:00:30.819667 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:00:30.819679 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:00:30.819690 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:00:30.819706 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:00:30.819718 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:00:30.819730 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:00:30.819741 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:00:30.819756 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.40883 (* 0.0454545 = 0.154947 loss) | |
| I0407 16:00:30.819771 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.96604 (* 0.0454545 = 0.180275 loss) | |
| I0407 16:00:30.819783 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.6224 (* 0.0454545 = 0.164655 loss) | |
| I0407 16:00:30.819797 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.83809 (* 0.0454545 = 0.174459 loss) | |
| I0407 16:00:30.819811 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.33461 (* 0.0454545 = 0.151573 loss) | |
| I0407 16:00:30.819825 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.34686 (* 0.0454545 = 0.106675 loss) | |
| I0407 16:00:30.819839 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.735187 (* 0.0454545 = 0.0334176 loss) | |
| I0407 16:00:30.819851 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.744243 (* 0.0454545 = 0.0338292 loss) | |
| I0407 16:00:30.819865 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.46134 (* 0.0454545 = 0.02097 loss) | |
| I0407 16:00:30.819880 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.00598256 (* 0.0454545 = 0.000271934 loss) | |
| I0407 16:00:30.819911 1004 solver.cpp:245] Train net output #32: loss/loss11 = 3.46396e-05 (* 0.0454545 = 1.57453e-06 loss) | |
| I0407 16:00:30.819926 1004 solver.cpp:245] Train net output #33: loss/loss12 = 3.69653e-05 (* 0.0454545 = 1.68024e-06 loss) | |
| I0407 16:00:30.819939 1004 solver.cpp:245] Train net output #34: loss/loss13 = 3.39169e-05 (* 0.0454545 = 1.54168e-06 loss) | |
| I0407 16:00:30.819953 1004 solver.cpp:245] Train net output #35: loss/loss14 = 3.49979e-05 (* 0.0454545 = 1.59081e-06 loss) | |
| I0407 16:00:30.819967 1004 solver.cpp:245] Train net output #36: loss/loss15 = 3.89146e-05 (* 0.0454545 = 1.76884e-06 loss) | |
| I0407 16:00:30.819982 1004 solver.cpp:245] Train net output #37: loss/loss16 = 3.79681e-05 (* 0.0454545 = 1.72582e-06 loss) | |
| I0407 16:00:30.819995 1004 solver.cpp:245] Train net output #38: loss/loss17 = 3.43271e-05 (* 0.0454545 = 1.56032e-06 loss) | |
| I0407 16:00:30.820009 1004 solver.cpp:245] Train net output #39: loss/loss18 = 3.51168e-05 (* 0.0454545 = 1.59622e-06 loss) | |
| I0407 16:00:30.820022 1004 solver.cpp:245] Train net output #40: loss/loss19 = 3.56241e-05 (* 0.0454545 = 1.61928e-06 loss) | |
| I0407 16:00:30.820036 1004 solver.cpp:245] Train net output #41: loss/loss20 = 3.63619e-05 (* 0.0454545 = 1.65281e-06 loss) | |
| I0407 16:00:30.820050 1004 solver.cpp:245] Train net output #42: loss/loss21 = 3.48487e-05 (* 0.0454545 = 1.58403e-06 loss) | |
| I0407 16:00:30.820063 1004 solver.cpp:245] Train net output #43: loss/loss22 = 3.80278e-05 (* 0.0454545 = 1.72854e-06 loss) | |
| I0407 16:00:30.820078 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:00:30.820091 1004 solver.cpp:245] Train net output #45: total_confidence = 1.67611e-05 | |
| I0407 16:00:30.820106 1004 sgd_solver.cpp:106] Iteration 35000, lr = 0.00093 | |
| I0407 16:01:08.781437 1004 solver.cpp:229] Iteration 35500, loss = 1.07319 | |
| I0407 16:01:08.781599 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:01:08.781621 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:01:08.781635 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 16:01:08.781647 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 16:01:08.781659 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 16:01:08.781672 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.1875 | |
| I0407 16:01:08.781683 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.5625 | |
| I0407 16:01:08.781695 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 16:01:08.781708 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.875 | |
| I0407 16:01:08.781719 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 16:01:08.781731 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:01:08.781743 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:01:08.781754 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:01:08.781766 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:01:08.781777 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:01:08.781790 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:01:08.781801 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:01:08.781813 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:01:08.781824 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:01:08.781836 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:01:08.781847 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:01:08.781858 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:01:08.781874 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.61963 (* 0.0454545 = 0.164529 loss) | |
| I0407 16:01:08.781888 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.73845 (* 0.0454545 = 0.169929 loss) | |
| I0407 16:01:08.781903 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.7416 (* 0.0454545 = 0.170073 loss) | |
| I0407 16:01:08.781916 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.72878 (* 0.0454545 = 0.16949 loss) | |
| I0407 16:01:08.781934 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.58579 (* 0.0454545 = 0.162991 loss) | |
| I0407 16:01:08.781947 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.49722 (* 0.0454545 = 0.158965 loss) | |
| I0407 16:01:08.781961 1004 solver.cpp:245] Train net output #28: loss/loss07 = 2.16429 (* 0.0454545 = 0.0983766 loss) | |
| I0407 16:01:08.781975 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.701459 (* 0.0454545 = 0.0318845 loss) | |
| I0407 16:01:08.781990 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.857992 (* 0.0454545 = 0.0389996 loss) | |
| I0407 16:01:08.782002 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.454029 (* 0.0454545 = 0.0206377 loss) | |
| I0407 16:01:08.782017 1004 solver.cpp:245] Train net output #32: loss/loss11 = 6.13262e-05 (* 0.0454545 = 2.78755e-06 loss) | |
| I0407 16:01:08.782032 1004 solver.cpp:245] Train net output #33: loss/loss12 = 5.91051e-05 (* 0.0454545 = 2.6866e-06 loss) | |
| I0407 16:01:08.782047 1004 solver.cpp:245] Train net output #34: loss/loss13 = 5.81736e-05 (* 0.0454545 = 2.64426e-06 loss) | |
| I0407 16:01:08.782060 1004 solver.cpp:245] Train net output #35: loss/loss14 = 6.09383e-05 (* 0.0454545 = 2.76992e-06 loss) | |
| I0407 16:01:08.782074 1004 solver.cpp:245] Train net output #36: loss/loss15 = 5.84718e-05 (* 0.0454545 = 2.65781e-06 loss) | |
| I0407 16:01:08.782088 1004 solver.cpp:245] Train net output #37: loss/loss16 = 5.63925e-05 (* 0.0454545 = 2.5633e-06 loss) | |
| I0407 16:01:08.782102 1004 solver.cpp:245] Train net output #38: loss/loss17 = 5.67836e-05 (* 0.0454545 = 2.58107e-06 loss) | |
| I0407 16:01:08.782130 1004 solver.cpp:245] Train net output #39: loss/loss18 = 5.91424e-05 (* 0.0454545 = 2.68829e-06 loss) | |
| I0407 16:01:08.782146 1004 solver.cpp:245] Train net output #40: loss/loss19 = 6.02566e-05 (* 0.0454545 = 2.73894e-06 loss) | |
| I0407 16:01:08.782160 1004 solver.cpp:245] Train net output #41: loss/loss20 = 5.99662e-05 (* 0.0454545 = 2.72574e-06 loss) | |
| I0407 16:01:08.782174 1004 solver.cpp:245] Train net output #42: loss/loss21 = 5.6903e-05 (* 0.0454545 = 2.5865e-06 loss) | |
| I0407 16:01:08.782189 1004 solver.cpp:245] Train net output #43: loss/loss22 = 5.65301e-05 (* 0.0454545 = 2.56955e-06 loss) | |
| I0407 16:01:08.782202 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:01:08.782213 1004 solver.cpp:245] Train net output #45: total_confidence = 1.13339e-05 | |
| I0407 16:01:08.782227 1004 sgd_solver.cpp:106] Iteration 35500, lr = 0.000929 | |
| I0407 16:01:47.479817 1004 solver.cpp:229] Iteration 36000, loss = 1.06957 | |
| I0407 16:01:47.479957 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:01:47.479979 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:01:47.479991 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:01:47.480005 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.25 | |
| I0407 16:01:47.480016 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.3125 | |
| I0407 16:01:47.480028 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5 | |
| I0407 16:01:47.480041 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.625 | |
| I0407 16:01:47.480052 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 16:01:47.480064 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.875 | |
| I0407 16:01:47.480077 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 16:01:47.480088 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:01:47.480100 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:01:47.480113 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:01:47.480124 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:01:47.480135 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:01:47.480147 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:01:47.480159 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:01:47.480170 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:01:47.480182 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:01:47.480193 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:01:47.480209 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:01:47.480221 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:01:47.480237 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.35107 (* 0.0454545 = 0.152321 loss) | |
| I0407 16:01:47.480252 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.4982 (* 0.0454545 = 0.159009 loss) | |
| I0407 16:01:47.480267 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.6186 (* 0.0454545 = 0.164482 loss) | |
| I0407 16:01:47.480280 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.32253 (* 0.0454545 = 0.151024 loss) | |
| I0407 16:01:47.480293 1004 solver.cpp:245] Train net output #26: loss/loss05 = 2.99503 (* 0.0454545 = 0.136138 loss) | |
| I0407 16:01:47.480309 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.42095 (* 0.0454545 = 0.110043 loss) | |
| I0407 16:01:47.480322 1004 solver.cpp:245] Train net output #28: loss/loss07 = 2.05899 (* 0.0454545 = 0.0935902 loss) | |
| I0407 16:01:47.480336 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.916541 (* 0.0454545 = 0.041661 loss) | |
| I0407 16:01:47.480350 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.980466 (* 0.0454545 = 0.0445666 loss) | |
| I0407 16:01:47.480365 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.330707 (* 0.0454545 = 0.0150321 loss) | |
| I0407 16:01:47.480378 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000527381 (* 0.0454545 = 2.39719e-05 loss) | |
| I0407 16:01:47.480393 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000528911 (* 0.0454545 = 2.40414e-05 loss) | |
| I0407 16:01:47.480407 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.00049466 (* 0.0454545 = 2.24845e-05 loss) | |
| I0407 16:01:47.480422 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00050295 (* 0.0454545 = 2.28614e-05 loss) | |
| I0407 16:01:47.480435 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000520558 (* 0.0454545 = 2.36617e-05 loss) | |
| I0407 16:01:47.480449 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000451005 (* 0.0454545 = 2.05002e-05 loss) | |
| I0407 16:01:47.480463 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000472989 (* 0.0454545 = 2.14995e-05 loss) | |
| I0407 16:01:47.480494 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000478207 (* 0.0454545 = 2.17367e-05 loss) | |
| I0407 16:01:47.480509 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000476372 (* 0.0454545 = 2.16533e-05 loss) | |
| I0407 16:01:47.480525 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000481872 (* 0.0454545 = 2.19033e-05 loss) | |
| I0407 16:01:47.480538 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000475384 (* 0.0454545 = 2.16083e-05 loss) | |
| I0407 16:01:47.480552 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000500647 (* 0.0454545 = 2.27567e-05 loss) | |
| I0407 16:01:47.480564 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:01:47.480576 1004 solver.cpp:245] Train net output #45: total_confidence = 2.44729e-05 | |
| I0407 16:01:47.480590 1004 sgd_solver.cpp:106] Iteration 36000, lr = 0.000928 | |
| I0407 16:02:25.781113 1004 solver.cpp:229] Iteration 36500, loss = 1.0704 | |
| I0407 16:02:25.781213 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:02:25.781232 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:02:25.781245 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:02:25.781257 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 16:02:25.781270 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 16:02:25.781281 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 16:02:25.781293 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.625 | |
| I0407 16:02:25.781311 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.75 | |
| I0407 16:02:25.781323 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:02:25.781335 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 16:02:25.781347 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:02:25.781358 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:02:25.781370 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:02:25.781381 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:02:25.781394 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:02:25.781404 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:02:25.781415 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:02:25.781427 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:02:25.781440 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:02:25.781450 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:02:25.781462 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:02:25.781473 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:02:25.781488 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.4227 (* 0.0454545 = 0.155577 loss) | |
| I0407 16:02:25.781503 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.89716 (* 0.0454545 = 0.177144 loss) | |
| I0407 16:02:25.781517 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.79062 (* 0.0454545 = 0.172301 loss) | |
| I0407 16:02:25.781532 1004 solver.cpp:245] Train net output #25: loss/loss04 = 4.01895 (* 0.0454545 = 0.18268 loss) | |
| I0407 16:02:25.781546 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.37214 (* 0.0454545 = 0.153279 loss) | |
| I0407 16:02:25.781560 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.82213 (* 0.0454545 = 0.128279 loss) | |
| I0407 16:02:25.781574 1004 solver.cpp:245] Train net output #28: loss/loss07 = 2.11171 (* 0.0454545 = 0.0959867 loss) | |
| I0407 16:02:25.781587 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.43358 (* 0.0454545 = 0.065163 loss) | |
| I0407 16:02:25.781600 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.501035 (* 0.0454545 = 0.0227743 loss) | |
| I0407 16:02:25.781615 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.575695 (* 0.0454545 = 0.026168 loss) | |
| I0407 16:02:25.781628 1004 solver.cpp:245] Train net output #32: loss/loss11 = 6.89812e-05 (* 0.0454545 = 3.13551e-06 loss) | |
| I0407 16:02:25.781643 1004 solver.cpp:245] Train net output #33: loss/loss12 = 7.05581e-05 (* 0.0454545 = 3.20719e-06 loss) | |
| I0407 16:02:25.781657 1004 solver.cpp:245] Train net output #34: loss/loss13 = 7.10164e-05 (* 0.0454545 = 3.22802e-06 loss) | |
| I0407 16:02:25.781672 1004 solver.cpp:245] Train net output #35: loss/loss14 = 6.98092e-05 (* 0.0454545 = 3.17314e-06 loss) | |
| I0407 16:02:25.781685 1004 solver.cpp:245] Train net output #36: loss/loss15 = 6.69948e-05 (* 0.0454545 = 3.04522e-06 loss) | |
| I0407 16:02:25.781699 1004 solver.cpp:245] Train net output #37: loss/loss16 = 6.82405e-05 (* 0.0454545 = 3.10184e-06 loss) | |
| I0407 16:02:25.781713 1004 solver.cpp:245] Train net output #38: loss/loss17 = 6.57243e-05 (* 0.0454545 = 2.98747e-06 loss) | |
| I0407 16:02:25.781744 1004 solver.cpp:245] Train net output #39: loss/loss18 = 7.01816e-05 (* 0.0454545 = 3.19007e-06 loss) | |
| I0407 16:02:25.781759 1004 solver.cpp:245] Train net output #40: loss/loss19 = 6.42002e-05 (* 0.0454545 = 2.91819e-06 loss) | |
| I0407 16:02:25.781774 1004 solver.cpp:245] Train net output #41: loss/loss20 = 6.60302e-05 (* 0.0454545 = 3.00137e-06 loss) | |
| I0407 16:02:25.781787 1004 solver.cpp:245] Train net output #42: loss/loss21 = 6.64808e-05 (* 0.0454545 = 3.02185e-06 loss) | |
| I0407 16:02:25.781801 1004 solver.cpp:245] Train net output #43: loss/loss22 = 7.20591e-05 (* 0.0454545 = 3.27541e-06 loss) | |
| I0407 16:02:25.781813 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:02:25.781824 1004 solver.cpp:245] Train net output #45: total_confidence = 6.1039e-06 | |
| I0407 16:02:25.781838 1004 sgd_solver.cpp:106] Iteration 36500, lr = 0.000927 | |
| I0407 16:03:04.271193 1004 solver.cpp:229] Iteration 37000, loss = 1.07532 | |
| I0407 16:03:04.271334 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:03:04.271354 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.125 | |
| I0407 16:03:04.271368 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:03:04.271380 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 16:03:04.271392 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 16:03:04.271404 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 16:03:04.271416 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 16:03:04.271428 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 16:03:04.271440 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:03:04.271451 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:03:04.271462 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:03:04.271474 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:03:04.271486 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:03:04.271497 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:03:04.271508 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:03:04.271520 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:03:04.271531 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:03:04.271543 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:03:04.271555 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:03:04.271566 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:03:04.271579 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:03:04.271589 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:03:04.271605 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.69983 (* 0.0454545 = 0.168174 loss) | |
| I0407 16:03:04.271620 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.56435 (* 0.0454545 = 0.162016 loss) | |
| I0407 16:03:04.271634 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.69629 (* 0.0454545 = 0.168013 loss) | |
| I0407 16:03:04.271647 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.9403 (* 0.0454545 = 0.179105 loss) | |
| I0407 16:03:04.271661 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.71244 (* 0.0454545 = 0.168747 loss) | |
| I0407 16:03:04.271675 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.21088 (* 0.0454545 = 0.145949 loss) | |
| I0407 16:03:04.271689 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.22517 (* 0.0454545 = 0.0556895 loss) | |
| I0407 16:03:04.271703 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.0887921 (* 0.0454545 = 0.004036 loss) | |
| I0407 16:03:04.271718 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0271758 (* 0.0454545 = 0.00123526 loss) | |
| I0407 16:03:04.271731 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0104897 (* 0.0454545 = 0.000476806 loss) | |
| I0407 16:03:04.271745 1004 solver.cpp:245] Train net output #32: loss/loss11 = 8.99646e-05 (* 0.0454545 = 4.0893e-06 loss) | |
| I0407 16:03:04.271760 1004 solver.cpp:245] Train net output #33: loss/loss12 = 8.67441e-05 (* 0.0454545 = 3.94291e-06 loss) | |
| I0407 16:03:04.271775 1004 solver.cpp:245] Train net output #34: loss/loss13 = 9.0617e-05 (* 0.0454545 = 4.11895e-06 loss) | |
| I0407 16:03:04.271788 1004 solver.cpp:245] Train net output #35: loss/loss14 = 8.62411e-05 (* 0.0454545 = 3.92005e-06 loss) | |
| I0407 16:03:04.271802 1004 solver.cpp:245] Train net output #36: loss/loss15 = 8.90103e-05 (* 0.0454545 = 4.04592e-06 loss) | |
| I0407 16:03:04.271816 1004 solver.cpp:245] Train net output #37: loss/loss16 = 8.43326e-05 (* 0.0454545 = 3.8333e-06 loss) | |
| I0407 16:03:04.271831 1004 solver.cpp:245] Train net output #38: loss/loss17 = 8.09221e-05 (* 0.0454545 = 3.67828e-06 loss) | |
| I0407 16:03:04.271863 1004 solver.cpp:245] Train net output #39: loss/loss18 = 8.43255e-05 (* 0.0454545 = 3.83298e-06 loss) | |
| I0407 16:03:04.271878 1004 solver.cpp:245] Train net output #40: loss/loss19 = 7.95242e-05 (* 0.0454545 = 3.61473e-06 loss) | |
| I0407 16:03:04.271893 1004 solver.cpp:245] Train net output #41: loss/loss20 = 8.17947e-05 (* 0.0454545 = 3.71794e-06 loss) | |
| I0407 16:03:04.271906 1004 solver.cpp:245] Train net output #42: loss/loss21 = 8.14441e-05 (* 0.0454545 = 3.702e-06 loss) | |
| I0407 16:03:04.271924 1004 solver.cpp:245] Train net output #43: loss/loss22 = 8.99716e-05 (* 0.0454545 = 4.08962e-06 loss) | |
| I0407 16:03:04.271936 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:03:04.271949 1004 solver.cpp:245] Train net output #45: total_confidence = 9.89308e-06 | |
| I0407 16:03:04.271962 1004 sgd_solver.cpp:106] Iteration 37000, lr = 0.000926 | |
| I0407 16:03:43.050057 1004 solver.cpp:229] Iteration 37500, loss = 1.06792 | |
| I0407 16:03:43.050225 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:03:43.050245 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:03:43.050258 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 16:03:43.050271 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 16:03:43.050282 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 16:03:43.050294 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5 | |
| I0407 16:03:43.050307 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 16:03:43.050319 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 16:03:43.050333 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:03:43.050343 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:03:43.050355 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:03:43.050367 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:03:43.050379 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:03:43.050390 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:03:43.050402 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:03:43.050415 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:03:43.050426 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:03:43.050437 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:03:43.050449 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:03:43.050460 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:03:43.050472 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:03:43.050484 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:03:43.050500 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.96255 (* 0.0454545 = 0.180116 loss) | |
| I0407 16:03:43.050514 1004 solver.cpp:245] Train net output #23: loss/loss02 = 4.01379 (* 0.0454545 = 0.182445 loss) | |
| I0407 16:03:43.050529 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.93083 (* 0.0454545 = 0.178674 loss) | |
| I0407 16:03:43.050542 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.69413 (* 0.0454545 = 0.167915 loss) | |
| I0407 16:03:43.050556 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.52237 (* 0.0454545 = 0.160108 loss) | |
| I0407 16:03:43.050570 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.67799 (* 0.0454545 = 0.121727 loss) | |
| I0407 16:03:43.050585 1004 solver.cpp:245] Train net output #28: loss/loss07 = 2.32817 (* 0.0454545 = 0.105826 loss) | |
| I0407 16:03:43.050598 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.95145 (* 0.0454545 = 0.0887024 loss) | |
| I0407 16:03:43.050612 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0350969 (* 0.0454545 = 0.00159531 loss) | |
| I0407 16:03:43.050627 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0133475 (* 0.0454545 = 0.000606704 loss) | |
| I0407 16:03:43.050642 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000163269 (* 0.0454545 = 7.4213e-06 loss) | |
| I0407 16:03:43.050657 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000159162 (* 0.0454545 = 7.23463e-06 loss) | |
| I0407 16:03:43.050670 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000166208 (* 0.0454545 = 7.55491e-06 loss) | |
| I0407 16:03:43.050684 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000157548 (* 0.0454545 = 7.16127e-06 loss) | |
| I0407 16:03:43.050698 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000169429 (* 0.0454545 = 7.70134e-06 loss) | |
| I0407 16:03:43.050714 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000160309 (* 0.0454545 = 7.28676e-06 loss) | |
| I0407 16:03:43.050727 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000163114 (* 0.0454545 = 7.41426e-06 loss) | |
| I0407 16:03:43.050755 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000151908 (* 0.0454545 = 6.90492e-06 loss) | |
| I0407 16:03:43.050770 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000154049 (* 0.0454545 = 7.00224e-06 loss) | |
| I0407 16:03:43.050784 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000167848 (* 0.0454545 = 7.62946e-06 loss) | |
| I0407 16:03:43.050798 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000153796 (* 0.0454545 = 6.99073e-06 loss) | |
| I0407 16:03:43.050812 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000149478 (* 0.0454545 = 6.79443e-06 loss) | |
| I0407 16:03:43.050824 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:03:43.050837 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000632564 | |
| I0407 16:03:43.050849 1004 sgd_solver.cpp:106] Iteration 37500, lr = 0.000925 | |
| I0407 16:04:22.870689 1004 solver.cpp:229] Iteration 38000, loss = 1.05927 | |
| I0407 16:04:22.870813 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 16:04:22.870832 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:04:22.870846 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:04:22.870857 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 16:04:22.870868 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 16:04:22.870882 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 16:04:22.870894 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.625 | |
| I0407 16:04:22.870905 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 16:04:22.870920 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:04:22.870932 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:04:22.870944 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:04:22.870956 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:04:22.870968 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:04:22.870980 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:04:22.870991 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:04:22.871003 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:04:22.871014 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:04:22.871026 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:04:22.871037 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:04:22.871048 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:04:22.871060 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:04:22.871073 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:04:22.871088 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.7483 (* 0.0454545 = 0.170377 loss) | |
| I0407 16:04:22.871103 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.80805 (* 0.0454545 = 0.173093 loss) | |
| I0407 16:04:22.871117 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.76246 (* 0.0454545 = 0.171021 loss) | |
| I0407 16:04:22.871131 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.89829 (* 0.0454545 = 0.177195 loss) | |
| I0407 16:04:22.871145 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.30599 (* 0.0454545 = 0.150272 loss) | |
| I0407 16:04:22.871158 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.89032 (* 0.0454545 = 0.131378 loss) | |
| I0407 16:04:22.871172 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.80525 (* 0.0454545 = 0.082057 loss) | |
| I0407 16:04:22.871186 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.650895 (* 0.0454545 = 0.0295861 loss) | |
| I0407 16:04:22.871199 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.33856 (* 0.0454545 = 0.0153891 loss) | |
| I0407 16:04:22.871213 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0254676 (* 0.0454545 = 0.00115762 loss) | |
| I0407 16:04:22.871228 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000282918 (* 0.0454545 = 1.28599e-05 loss) | |
| I0407 16:04:22.871243 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000272587 (* 0.0454545 = 1.23903e-05 loss) | |
| I0407 16:04:22.871258 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000275957 (* 0.0454545 = 1.25435e-05 loss) | |
| I0407 16:04:22.871271 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000276871 (* 0.0454545 = 1.25851e-05 loss) | |
| I0407 16:04:22.871296 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000254841 (* 0.0454545 = 1.15837e-05 loss) | |
| I0407 16:04:22.871345 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000266802 (* 0.0454545 = 1.21274e-05 loss) | |
| I0407 16:04:22.871362 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.00026762 (* 0.0454545 = 1.21646e-05 loss) | |
| I0407 16:04:22.871618 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000269743 (* 0.0454545 = 1.2261e-05 loss) | |
| I0407 16:04:22.871634 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000262552 (* 0.0454545 = 1.19342e-05 loss) | |
| I0407 16:04:22.871649 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000271711 (* 0.0454545 = 1.23505e-05 loss) | |
| I0407 16:04:22.871664 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000274312 (* 0.0454545 = 1.24687e-05 loss) | |
| I0407 16:04:22.871677 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000272627 (* 0.0454545 = 1.23921e-05 loss) | |
| I0407 16:04:22.871690 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:04:22.871701 1004 solver.cpp:245] Train net output #45: total_confidence = 1.69649e-05 | |
| I0407 16:04:22.871716 1004 sgd_solver.cpp:106] Iteration 38000, lr = 0.000924 | |
| I0407 16:05:01.672406 1004 solver.cpp:229] Iteration 38500, loss = 1.07025 | |
| I0407 16:05:01.672608 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 16:05:01.672629 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:05:01.672646 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:05:01.672659 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 16:05:01.672670 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 16:05:01.672683 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 16:05:01.672695 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 16:05:01.672706 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:05:01.672719 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:05:01.672730 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:05:01.672741 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:05:01.672754 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:05:01.672765 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:05:01.672776 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:05:01.672787 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:05:01.672799 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:05:01.672811 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:05:01.672821 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:05:01.672833 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:05:01.672844 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:05:01.672857 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:05:01.672868 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:05:01.672883 1004 solver.cpp:245] Train net output #22: loss/loss01 = 4.32815 (* 0.0454545 = 0.196734 loss) | |
| I0407 16:05:01.672897 1004 solver.cpp:245] Train net output #23: loss/loss02 = 4.14833 (* 0.0454545 = 0.188561 loss) | |
| I0407 16:05:01.672911 1004 solver.cpp:245] Train net output #24: loss/loss03 = 4.12589 (* 0.0454545 = 0.18754 loss) | |
| I0407 16:05:01.672925 1004 solver.cpp:245] Train net output #25: loss/loss04 = 4.04115 (* 0.0454545 = 0.183688 loss) | |
| I0407 16:05:01.672938 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.68495 (* 0.0454545 = 0.167498 loss) | |
| I0407 16:05:01.672952 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.82666 (* 0.0454545 = 0.128484 loss) | |
| I0407 16:05:01.672966 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.69564 (* 0.0454545 = 0.0770745 loss) | |
| I0407 16:05:01.672979 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.592927 (* 0.0454545 = 0.0269512 loss) | |
| I0407 16:05:01.672994 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0353696 (* 0.0454545 = 0.00160771 loss) | |
| I0407 16:05:01.673008 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0111786 (* 0.0454545 = 0.00050812 loss) | |
| I0407 16:05:01.673022 1004 solver.cpp:245] Train net output #32: loss/loss11 = 5.69299e-05 (* 0.0454545 = 2.58772e-06 loss) | |
| I0407 16:05:01.673038 1004 solver.cpp:245] Train net output #33: loss/loss12 = 5.92631e-05 (* 0.0454545 = 2.69378e-06 loss) | |
| I0407 16:05:01.673051 1004 solver.cpp:245] Train net output #34: loss/loss13 = 5.76159e-05 (* 0.0454545 = 2.61891e-06 loss) | |
| I0407 16:05:01.673065 1004 solver.cpp:245] Train net output #35: loss/loss14 = 5.8212e-05 (* 0.0454545 = 2.646e-06 loss) | |
| I0407 16:05:01.673082 1004 solver.cpp:245] Train net output #36: loss/loss15 = 6.02878e-05 (* 0.0454545 = 2.74035e-06 loss) | |
| I0407 16:05:01.673096 1004 solver.cpp:245] Train net output #37: loss/loss16 = 5.41205e-05 (* 0.0454545 = 2.46002e-06 loss) | |
| I0407 16:05:01.673110 1004 solver.cpp:245] Train net output #38: loss/loss17 = 6.03106e-05 (* 0.0454545 = 2.74139e-06 loss) | |
| I0407 16:05:01.673143 1004 solver.cpp:245] Train net output #39: loss/loss18 = 6.05044e-05 (* 0.0454545 = 2.7502e-06 loss) | |
| I0407 16:05:01.673158 1004 solver.cpp:245] Train net output #40: loss/loss19 = 5.82125e-05 (* 0.0454545 = 2.64602e-06 loss) | |
| I0407 16:05:01.673172 1004 solver.cpp:245] Train net output #41: loss/loss20 = 5.5611e-05 (* 0.0454545 = 2.52777e-06 loss) | |
| I0407 16:05:01.673187 1004 solver.cpp:245] Train net output #42: loss/loss21 = 5.69009e-05 (* 0.0454545 = 2.5864e-06 loss) | |
| I0407 16:05:01.673200 1004 solver.cpp:245] Train net output #43: loss/loss22 = 5.50002e-05 (* 0.0454545 = 2.50001e-06 loss) | |
| I0407 16:05:01.673213 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:05:01.673224 1004 solver.cpp:245] Train net output #45: total_confidence = 2.14057e-05 | |
| I0407 16:05:01.673238 1004 sgd_solver.cpp:106] Iteration 38500, lr = 0.000923 | |
| I0407 16:05:40.713317 1004 solver.cpp:229] Iteration 39000, loss = 1.06893 | |
| I0407 16:05:40.713433 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:05:40.713454 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:05:40.713467 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:05:40.713480 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 16:05:40.713492 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 16:05:40.713505 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 16:05:40.713517 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 16:05:40.713529 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 16:05:40.713541 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:05:40.713553 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:05:40.713565 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:05:40.713577 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:05:40.713588 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:05:40.713600 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:05:40.713611 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:05:40.713624 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:05:40.713634 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:05:40.713646 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:05:40.713659 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:05:40.713671 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:05:40.713682 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:05:40.713695 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:05:40.713709 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.7047 (* 0.0454545 = 0.168396 loss) | |
| I0407 16:05:40.713723 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.86313 (* 0.0454545 = 0.175597 loss) | |
| I0407 16:05:40.713737 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.92121 (* 0.0454545 = 0.178237 loss) | |
| I0407 16:05:40.713752 1004 solver.cpp:245] Train net output #25: loss/loss04 = 4.12071 (* 0.0454545 = 0.187305 loss) | |
| I0407 16:05:40.713765 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.3211 (* 0.0454545 = 0.150959 loss) | |
| I0407 16:05:40.713779 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.6256 (* 0.0454545 = 0.119346 loss) | |
| I0407 16:05:40.713793 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.56828 (* 0.0454545 = 0.0712855 loss) | |
| I0407 16:05:40.713806 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.43282 (* 0.0454545 = 0.0651281 loss) | |
| I0407 16:05:40.713820 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.804228 (* 0.0454545 = 0.0365558 loss) | |
| I0407 16:05:40.713835 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0217734 (* 0.0454545 = 0.000989699 loss) | |
| I0407 16:05:40.713850 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000154827 (* 0.0454545 = 7.03761e-06 loss) | |
| I0407 16:05:40.713863 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000155642 (* 0.0454545 = 7.07463e-06 loss) | |
| I0407 16:05:40.713877 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000156319 (* 0.0454545 = 7.10543e-06 loss) | |
| I0407 16:05:40.713891 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000146421 (* 0.0454545 = 6.6555e-06 loss) | |
| I0407 16:05:40.713906 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000162729 (* 0.0454545 = 7.39677e-06 loss) | |
| I0407 16:05:40.713922 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000153643 (* 0.0454545 = 6.98379e-06 loss) | |
| I0407 16:05:40.713937 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000147856 (* 0.0454545 = 6.72074e-06 loss) | |
| I0407 16:05:40.713968 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000150573 (* 0.0454545 = 6.84421e-06 loss) | |
| I0407 16:05:40.713984 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000154437 (* 0.0454545 = 7.01988e-06 loss) | |
| I0407 16:05:40.713997 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000148991 (* 0.0454545 = 6.77233e-06 loss) | |
| I0407 16:05:40.714011 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000161085 (* 0.0454545 = 7.32204e-06 loss) | |
| I0407 16:05:40.714025 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000156292 (* 0.0454545 = 7.10418e-06 loss) | |
| I0407 16:05:40.714037 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:05:40.714049 1004 solver.cpp:245] Train net output #45: total_confidence = 1.30095e-05 | |
| I0407 16:05:40.714062 1004 sgd_solver.cpp:106] Iteration 39000, lr = 0.000922 | |
| I0407 16:06:19.355815 1004 solver.cpp:229] Iteration 39500, loss = 1.06295 | |
| I0407 16:06:19.355947 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.25 | |
| I0407 16:06:19.355965 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:06:19.355979 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:06:19.355991 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 16:06:19.356004 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 16:06:19.356016 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 16:06:19.356029 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.5625 | |
| I0407 16:06:19.356040 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.75 | |
| I0407 16:06:19.356053 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.8125 | |
| I0407 16:06:19.356065 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.875 | |
| I0407 16:06:19.356076 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:06:19.356088 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:06:19.356101 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:06:19.356112 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:06:19.356122 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:06:19.356134 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:06:19.356145 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:06:19.356158 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:06:19.356168 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:06:19.356180 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:06:19.356191 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:06:19.356204 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:06:19.356218 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.38575 (* 0.0454545 = 0.153898 loss) | |
| I0407 16:06:19.356233 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.53227 (* 0.0454545 = 0.160558 loss) | |
| I0407 16:06:19.356247 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.46955 (* 0.0454545 = 0.157707 loss) | |
| I0407 16:06:19.356261 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.67046 (* 0.0454545 = 0.166839 loss) | |
| I0407 16:06:19.356274 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.25127 (* 0.0454545 = 0.147785 loss) | |
| I0407 16:06:19.356288 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.67588 (* 0.0454545 = 0.121631 loss) | |
| I0407 16:06:19.356302 1004 solver.cpp:245] Train net output #28: loss/loss07 = 2.21219 (* 0.0454545 = 0.100554 loss) | |
| I0407 16:06:19.356315 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.22579 (* 0.0454545 = 0.0557178 loss) | |
| I0407 16:06:19.356329 1004 solver.cpp:245] Train net output #30: loss/loss09 = 1.07351 (* 0.0454545 = 0.0487961 loss) | |
| I0407 16:06:19.356343 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.758591 (* 0.0454545 = 0.0344814 loss) | |
| I0407 16:06:19.356358 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000124926 (* 0.0454545 = 5.67844e-06 loss) | |
| I0407 16:06:19.356371 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000127787 (* 0.0454545 = 5.80852e-06 loss) | |
| I0407 16:06:19.356386 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000123442 (* 0.0454545 = 5.61099e-06 loss) | |
| I0407 16:06:19.356400 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000123024 (* 0.0454545 = 5.592e-06 loss) | |
| I0407 16:06:19.356415 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000132108 (* 0.0454545 = 6.0049e-06 loss) | |
| I0407 16:06:19.356429 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000119654 (* 0.0454545 = 5.43881e-06 loss) | |
| I0407 16:06:19.356443 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000125204 (* 0.0454545 = 5.69111e-06 loss) | |
| I0407 16:06:19.356472 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000129486 (* 0.0454545 = 5.88573e-06 loss) | |
| I0407 16:06:19.356487 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000118413 (* 0.0454545 = 5.3824e-06 loss) | |
| I0407 16:06:19.356500 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000123289 (* 0.0454545 = 5.60407e-06 loss) | |
| I0407 16:06:19.356514 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000130508 (* 0.0454545 = 5.93217e-06 loss) | |
| I0407 16:06:19.356528 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000124654 (* 0.0454545 = 5.66611e-06 loss) | |
| I0407 16:06:19.356540 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:06:19.356552 1004 solver.cpp:245] Train net output #45: total_confidence = 2.657e-05 | |
| I0407 16:06:19.356565 1004 sgd_solver.cpp:106] Iteration 39500, lr = 0.000921 | |
| I0407 16:06:58.203783 1004 solver.cpp:338] Iteration 40000, Testing net (#0) | |
| I0407 16:07:06.180579 1004 solver.cpp:393] Test loss: 0.939431 | |
| I0407 16:07:06.180631 1004 solver.cpp:406] Test net output #0: loss/accuracy01 = 0.317 | |
| I0407 16:07:06.180649 1004 solver.cpp:406] Test net output #1: loss/accuracy02 = 0.085 | |
| I0407 16:07:06.180661 1004 solver.cpp:406] Test net output #2: loss/accuracy03 = 0.028 | |
| I0407 16:07:06.180673 1004 solver.cpp:406] Test net output #3: loss/accuracy04 = 0.084 | |
| I0407 16:07:06.180685 1004 solver.cpp:406] Test net output #4: loss/accuracy05 = 0.212 | |
| I0407 16:07:06.180696 1004 solver.cpp:406] Test net output #5: loss/accuracy06 = 0.5 | |
| I0407 16:07:06.180708 1004 solver.cpp:406] Test net output #6: loss/accuracy07 = 0.893 | |
| I0407 16:07:06.180719 1004 solver.cpp:406] Test net output #7: loss/accuracy08 = 0.97 | |
| I0407 16:07:06.180730 1004 solver.cpp:406] Test net output #8: loss/accuracy09 = 0.995 | |
| I0407 16:07:06.180742 1004 solver.cpp:406] Test net output #9: loss/accuracy10 = 0.998 | |
| I0407 16:07:06.180752 1004 solver.cpp:406] Test net output #10: loss/accuracy11 = 1 | |
| I0407 16:07:06.180764 1004 solver.cpp:406] Test net output #11: loss/accuracy12 = 1 | |
| I0407 16:07:06.180776 1004 solver.cpp:406] Test net output #12: loss/accuracy13 = 1 | |
| I0407 16:07:06.180788 1004 solver.cpp:406] Test net output #13: loss/accuracy14 = 1 | |
| I0407 16:07:06.180799 1004 solver.cpp:406] Test net output #14: loss/accuracy15 = 1 | |
| I0407 16:07:06.180809 1004 solver.cpp:406] Test net output #15: loss/accuracy16 = 1 | |
| I0407 16:07:06.180820 1004 solver.cpp:406] Test net output #16: loss/accuracy17 = 1 | |
| I0407 16:07:06.180830 1004 solver.cpp:406] Test net output #17: loss/accuracy18 = 1 | |
| I0407 16:07:06.180842 1004 solver.cpp:406] Test net output #18: loss/accuracy19 = 1 | |
| I0407 16:07:06.180853 1004 solver.cpp:406] Test net output #19: loss/accuracy20 = 1 | |
| I0407 16:07:06.180865 1004 solver.cpp:406] Test net output #20: loss/accuracy21 = 1 | |
| I0407 16:07:06.180876 1004 solver.cpp:406] Test net output #21: loss/accuracy22 = 1 | |
| I0407 16:07:06.180889 1004 solver.cpp:406] Test net output #22: loss/loss01 = 3.14004 (* 0.0454545 = 0.142729 loss) | |
| I0407 16:07:06.180903 1004 solver.cpp:406] Test net output #23: loss/loss02 = 3.38375 (* 0.0454545 = 0.153807 loss) | |
| I0407 16:07:06.180919 1004 solver.cpp:406] Test net output #24: loss/loss03 = 3.51855 (* 0.0454545 = 0.159934 loss) | |
| I0407 16:07:06.180934 1004 solver.cpp:406] Test net output #25: loss/loss04 = 3.46958 (* 0.0454545 = 0.157708 loss) | |
| I0407 16:07:06.180948 1004 solver.cpp:406] Test net output #26: loss/loss05 = 3.39204 (* 0.0454545 = 0.154184 loss) | |
| I0407 16:07:06.180961 1004 solver.cpp:406] Test net output #27: loss/loss06 = 2.44867 (* 0.0454545 = 0.111303 loss) | |
| I0407 16:07:06.180974 1004 solver.cpp:406] Test net output #28: loss/loss07 = 0.859365 (* 0.0454545 = 0.0390621 loss) | |
| I0407 16:07:06.180989 1004 solver.cpp:406] Test net output #29: loss/loss08 = 0.301124 (* 0.0454545 = 0.0136874 loss) | |
| I0407 16:07:06.181001 1004 solver.cpp:406] Test net output #30: loss/loss09 = 0.0667845 (* 0.0454545 = 0.00303566 loss) | |
| I0407 16:07:06.181015 1004 solver.cpp:406] Test net output #31: loss/loss10 = 0.0329036 (* 0.0454545 = 0.00149562 loss) | |
| I0407 16:07:06.181030 1004 solver.cpp:406] Test net output #32: loss/loss11 = 0.00457309 (* 0.0454545 = 0.000207868 loss) | |
| I0407 16:07:06.181043 1004 solver.cpp:406] Test net output #33: loss/loss12 = 0.00456071 (* 0.0454545 = 0.000207305 loss) | |
| I0407 16:07:06.181056 1004 solver.cpp:406] Test net output #34: loss/loss13 = 0.00456978 (* 0.0454545 = 0.000207717 loss) | |
| I0407 16:07:06.181071 1004 solver.cpp:406] Test net output #35: loss/loss14 = 0.00455632 (* 0.0454545 = 0.000207105 loss) | |
| I0407 16:07:06.181084 1004 solver.cpp:406] Test net output #36: loss/loss15 = 0.00457842 (* 0.0454545 = 0.00020811 loss) | |
| I0407 16:07:06.181097 1004 solver.cpp:406] Test net output #37: loss/loss16 = 0.00452361 (* 0.0454545 = 0.000205618 loss) | |
| I0407 16:07:06.181112 1004 solver.cpp:406] Test net output #38: loss/loss17 = 0.00455762 (* 0.0454545 = 0.000207165 loss) | |
| I0407 16:07:06.181162 1004 solver.cpp:406] Test net output #39: loss/loss18 = 0.00454306 (* 0.0454545 = 0.000206503 loss) | |
| I0407 16:07:06.181177 1004 solver.cpp:406] Test net output #40: loss/loss19 = 0.00453494 (* 0.0454545 = 0.000206134 loss) | |
| I0407 16:07:06.181190 1004 solver.cpp:406] Test net output #41: loss/loss20 = 0.00456265 (* 0.0454545 = 0.000207393 loss) | |
| I0407 16:07:06.181205 1004 solver.cpp:406] Test net output #42: loss/loss21 = 0.00456196 (* 0.0454545 = 0.000207362 loss) | |
| I0407 16:07:06.181218 1004 solver.cpp:406] Test net output #43: loss/loss22 = 0.00455103 (* 0.0454545 = 0.000206865 loss) | |
| I0407 16:07:06.181229 1004 solver.cpp:406] Test net output #44: total_accuracy = 0 | |
| I0407 16:07:06.181241 1004 solver.cpp:406] Test net output #45: total_confidence = 0.000257721 | |
| I0407 16:07:06.203117 1004 solver.cpp:229] Iteration 40000, loss = 1.06022 | |
| I0407 16:07:06.203155 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 16:07:06.203171 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:07:06.203183 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:07:06.203196 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 16:07:06.203207 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 16:07:06.203219 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 16:07:06.203232 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 16:07:06.203243 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:07:06.203254 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:07:06.203266 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:07:06.203277 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:07:06.203289 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:07:06.203327 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:07:06.203352 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:07:06.203368 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:07:06.203380 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:07:06.203392 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:07:06.203404 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:07:06.203415 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:07:06.203428 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:07:06.203438 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:07:06.203450 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:07:06.203465 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.65941 (* 0.0454545 = 0.166337 loss) | |
| I0407 16:07:06.203480 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.58592 (* 0.0454545 = 0.162997 loss) | |
| I0407 16:07:06.203493 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.67902 (* 0.0454545 = 0.167228 loss) | |
| I0407 16:07:06.203506 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.73792 (* 0.0454545 = 0.169905 loss) | |
| I0407 16:07:06.203521 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.16956 (* 0.0454545 = 0.144071 loss) | |
| I0407 16:07:06.203534 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.79855 (* 0.0454545 = 0.127207 loss) | |
| I0407 16:07:06.203548 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.929474 (* 0.0454545 = 0.0422488 loss) | |
| I0407 16:07:06.203562 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.337123 (* 0.0454545 = 0.0153238 loss) | |
| I0407 16:07:06.203577 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0462546 (* 0.0454545 = 0.00210248 loss) | |
| I0407 16:07:06.203590 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0192038 (* 0.0454545 = 0.000872901 loss) | |
| I0407 16:07:06.203622 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000301373 (* 0.0454545 = 1.36988e-05 loss) | |
| I0407 16:07:06.203637 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000322732 (* 0.0454545 = 1.46696e-05 loss) | |
| I0407 16:07:06.203651 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000318003 (* 0.0454545 = 1.44547e-05 loss) | |
| I0407 16:07:06.203666 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000290362 (* 0.0454545 = 1.31983e-05 loss) | |
| I0407 16:07:06.203680 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000312836 (* 0.0454545 = 1.42198e-05 loss) | |
| I0407 16:07:06.203693 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000285979 (* 0.0454545 = 1.29991e-05 loss) | |
| I0407 16:07:06.203708 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000314881 (* 0.0454545 = 1.43128e-05 loss) | |
| I0407 16:07:06.203722 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000284317 (* 0.0454545 = 1.29235e-05 loss) | |
| I0407 16:07:06.203737 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000292348 (* 0.0454545 = 1.32885e-05 loss) | |
| I0407 16:07:06.203750 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000320764 (* 0.0454545 = 1.45802e-05 loss) | |
| I0407 16:07:06.203776 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000300887 (* 0.0454545 = 1.36767e-05 loss) | |
| I0407 16:07:06.203799 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000313816 (* 0.0454545 = 1.42644e-05 loss) | |
| I0407 16:07:06.203811 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:07:06.203824 1004 solver.cpp:245] Train net output #45: total_confidence = 3.82984e-05 | |
| I0407 16:07:06.203838 1004 sgd_solver.cpp:106] Iteration 40000, lr = 0.00092 | |
| I0407 16:07:44.647320 1004 solver.cpp:229] Iteration 40500, loss = 1.06391 | |
| I0407 16:07:44.647467 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:07:44.647488 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:07:44.647501 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:07:44.647513 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 16:07:44.647526 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 16:07:44.647537 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.25 | |
| I0407 16:07:44.647549 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 16:07:44.647562 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.75 | |
| I0407 16:07:44.647572 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:07:44.647584 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:07:44.647596 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:07:44.647608 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:07:44.647619 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:07:44.647630 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:07:44.647642 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:07:44.647653 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:07:44.647665 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:07:44.647677 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:07:44.647688 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:07:44.647701 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:07:44.647711 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:07:44.647723 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:07:44.647739 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.64611 (* 0.0454545 = 0.165732 loss) | |
| I0407 16:07:44.647753 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.55214 (* 0.0454545 = 0.161461 loss) | |
| I0407 16:07:44.647768 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.64754 (* 0.0454545 = 0.165797 loss) | |
| I0407 16:07:44.647781 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.44229 (* 0.0454545 = 0.156468 loss) | |
| I0407 16:07:44.647794 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.39118 (* 0.0454545 = 0.154145 loss) | |
| I0407 16:07:44.647809 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.25023 (* 0.0454545 = 0.147738 loss) | |
| I0407 16:07:44.647822 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.66995 (* 0.0454545 = 0.0759069 loss) | |
| I0407 16:07:44.647836 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.53455 (* 0.0454545 = 0.0697521 loss) | |
| I0407 16:07:44.647850 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.196199 (* 0.0454545 = 0.00891812 loss) | |
| I0407 16:07:44.647864 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.12236 (* 0.0454545 = 0.00556184 loss) | |
| I0407 16:07:44.647879 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.00695313 (* 0.0454545 = 0.000316051 loss) | |
| I0407 16:07:44.647893 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00701901 (* 0.0454545 = 0.000319046 loss) | |
| I0407 16:07:44.647908 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.00688168 (* 0.0454545 = 0.000312803 loss) | |
| I0407 16:07:44.647925 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00690719 (* 0.0454545 = 0.000313963 loss) | |
| I0407 16:07:44.647940 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.00729464 (* 0.0454545 = 0.000331575 loss) | |
| I0407 16:07:44.647955 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.00701626 (* 0.0454545 = 0.000318921 loss) | |
| I0407 16:07:44.647969 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.00686801 (* 0.0454545 = 0.000312182 loss) | |
| I0407 16:07:44.648000 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.00684125 (* 0.0454545 = 0.000310966 loss) | |
| I0407 16:07:44.648015 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00700806 (* 0.0454545 = 0.000318548 loss) | |
| I0407 16:07:44.648030 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.00697584 (* 0.0454545 = 0.000317084 loss) | |
| I0407 16:07:44.648043 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00662426 (* 0.0454545 = 0.000301103 loss) | |
| I0407 16:07:44.648057 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00700544 (* 0.0454545 = 0.000318429 loss) | |
| I0407 16:07:44.648069 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:07:44.648082 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000141929 | |
| I0407 16:07:44.648094 1004 sgd_solver.cpp:106] Iteration 40500, lr = 0.000919 | |
| I0407 16:08:23.322471 1004 solver.cpp:229] Iteration 41000, loss = 1.06258 | |
| I0407 16:08:23.322621 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.1875 | |
| I0407 16:08:23.322643 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:08:23.322655 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:08:23.322667 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 16:08:23.322680 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.3125 | |
| I0407 16:08:23.322692 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 16:08:23.322705 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.5625 | |
| I0407 16:08:23.322716 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 16:08:23.322728 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.875 | |
| I0407 16:08:23.322741 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 16:08:23.322752 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:08:23.322764 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:08:23.322777 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:08:23.322788 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:08:23.322798 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:08:23.322810 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:08:23.322823 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:08:23.322834 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:08:23.322845 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:08:23.322856 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:08:23.322868 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:08:23.322880 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:08:23.322896 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.39499 (* 0.0454545 = 0.154318 loss) | |
| I0407 16:08:23.322911 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.44165 (* 0.0454545 = 0.156439 loss) | |
| I0407 16:08:23.322927 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.39879 (* 0.0454545 = 0.15449 loss) | |
| I0407 16:08:23.322942 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.48506 (* 0.0454545 = 0.158412 loss) | |
| I0407 16:08:23.322957 1004 solver.cpp:245] Train net output #26: loss/loss05 = 2.93749 (* 0.0454545 = 0.133522 loss) | |
| I0407 16:08:23.322970 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.71821 (* 0.0454545 = 0.123555 loss) | |
| I0407 16:08:23.322984 1004 solver.cpp:245] Train net output #28: loss/loss07 = 2.23014 (* 0.0454545 = 0.10137 loss) | |
| I0407 16:08:23.322999 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.752962 (* 0.0454545 = 0.0342256 loss) | |
| I0407 16:08:23.323011 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.78063 (* 0.0454545 = 0.0354832 loss) | |
| I0407 16:08:23.323025 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.542277 (* 0.0454545 = 0.024649 loss) | |
| I0407 16:08:23.323040 1004 solver.cpp:245] Train net output #32: loss/loss11 = 6.2866e-05 (* 0.0454545 = 2.85755e-06 loss) | |
| I0407 16:08:23.323053 1004 solver.cpp:245] Train net output #33: loss/loss12 = 5.79395e-05 (* 0.0454545 = 2.63362e-06 loss) | |
| I0407 16:08:23.323067 1004 solver.cpp:245] Train net output #34: loss/loss13 = 6.14047e-05 (* 0.0454545 = 2.79112e-06 loss) | |
| I0407 16:08:23.323081 1004 solver.cpp:245] Train net output #35: loss/loss14 = 6.04802e-05 (* 0.0454545 = 2.7491e-06 loss) | |
| I0407 16:08:23.323096 1004 solver.cpp:245] Train net output #36: loss/loss15 = 6.42263e-05 (* 0.0454545 = 2.91938e-06 loss) | |
| I0407 16:08:23.323110 1004 solver.cpp:245] Train net output #37: loss/loss16 = 5.5759e-05 (* 0.0454545 = 2.5345e-06 loss) | |
| I0407 16:08:23.323124 1004 solver.cpp:245] Train net output #38: loss/loss17 = 6.2706e-05 (* 0.0454545 = 2.85027e-06 loss) | |
| I0407 16:08:23.323153 1004 solver.cpp:245] Train net output #39: loss/loss18 = 6.3093e-05 (* 0.0454545 = 2.86786e-06 loss) | |
| I0407 16:08:23.323168 1004 solver.cpp:245] Train net output #40: loss/loss19 = 5.58782e-05 (* 0.0454545 = 2.53992e-06 loss) | |
| I0407 16:08:23.323182 1004 solver.cpp:245] Train net output #41: loss/loss20 = 5.92807e-05 (* 0.0454545 = 2.69458e-06 loss) | |
| I0407 16:08:23.323196 1004 solver.cpp:245] Train net output #42: loss/loss21 = 6.09655e-05 (* 0.0454545 = 2.77116e-06 loss) | |
| I0407 16:08:23.323210 1004 solver.cpp:245] Train net output #43: loss/loss22 = 6.45161e-05 (* 0.0454545 = 2.93255e-06 loss) | |
| I0407 16:08:23.323222 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:08:23.323233 1004 solver.cpp:245] Train net output #45: total_confidence = 9.37075e-05 | |
| I0407 16:08:23.323247 1004 sgd_solver.cpp:106] Iteration 41000, lr = 0.000918 | |
| I0407 16:09:01.847571 1004 solver.cpp:229] Iteration 41500, loss = 1.05284 | |
| I0407 16:09:01.847707 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:09:01.847726 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:09:01.847740 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:09:01.847753 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 16:09:01.847764 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.0625 | |
| I0407 16:09:01.847777 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.25 | |
| I0407 16:09:01.847790 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 16:09:01.847801 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 16:09:01.847812 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:09:01.847825 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:09:01.847836 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:09:01.847847 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:09:01.847858 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:09:01.847870 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:09:01.847882 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:09:01.847893 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:09:01.847905 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:09:01.847919 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:09:01.847931 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:09:01.847944 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:09:01.847955 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:09:01.847967 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:09:01.847983 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.28541 (* 0.0454545 = 0.149337 loss) | |
| I0407 16:09:01.847997 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.63995 (* 0.0454545 = 0.165452 loss) | |
| I0407 16:09:01.848012 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.63572 (* 0.0454545 = 0.16526 loss) | |
| I0407 16:09:01.848026 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.60396 (* 0.0454545 = 0.163817 loss) | |
| I0407 16:09:01.848039 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.73622 (* 0.0454545 = 0.169828 loss) | |
| I0407 16:09:01.848053 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.14064 (* 0.0454545 = 0.142756 loss) | |
| I0407 16:09:01.848067 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.20674 (* 0.0454545 = 0.0548516 loss) | |
| I0407 16:09:01.848081 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.165798 (* 0.0454545 = 0.00753627 loss) | |
| I0407 16:09:01.848095 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0687741 (* 0.0454545 = 0.00312609 loss) | |
| I0407 16:09:01.848109 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0397439 (* 0.0454545 = 0.00180654 loss) | |
| I0407 16:09:01.848124 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.00213319 (* 0.0454545 = 9.69631e-05 loss) | |
| I0407 16:09:01.848139 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00213393 (* 0.0454545 = 9.69968e-05 loss) | |
| I0407 16:09:01.848152 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.00220009 (* 0.0454545 = 0.000100004 loss) | |
| I0407 16:09:01.848167 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.0020297 (* 0.0454545 = 9.2259e-05 loss) | |
| I0407 16:09:01.848181 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.00210333 (* 0.0454545 = 9.5606e-05 loss) | |
| I0407 16:09:01.848196 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.00200686 (* 0.0454545 = 9.1221e-05 loss) | |
| I0407 16:09:01.848211 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.00202312 (* 0.0454545 = 9.19602e-05 loss) | |
| I0407 16:09:01.848240 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.00209057 (* 0.0454545 = 9.5026e-05 loss) | |
| I0407 16:09:01.848255 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00207808 (* 0.0454545 = 9.44583e-05 loss) | |
| I0407 16:09:01.848269 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.00213473 (* 0.0454545 = 9.70332e-05 loss) | |
| I0407 16:09:01.848284 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00195718 (* 0.0454545 = 8.89625e-05 loss) | |
| I0407 16:09:01.848297 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00205691 (* 0.0454545 = 9.34957e-05 loss) | |
| I0407 16:09:01.848309 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:09:01.848321 1004 solver.cpp:245] Train net output #45: total_confidence = 1.05152e-05 | |
| I0407 16:09:01.848336 1004 sgd_solver.cpp:106] Iteration 41500, lr = 0.000917 | |
| I0407 16:09:41.206471 1004 solver.cpp:229] Iteration 42000, loss = 1.05382 | |
| I0407 16:09:41.206595 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:09:41.206624 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:09:41.206648 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:09:41.206671 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 16:09:41.206693 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.0625 | |
| I0407 16:09:41.206714 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 16:09:41.206738 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 16:09:41.206761 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 16:09:41.206784 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:09:41.206806 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:09:41.206827 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:09:41.206850 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:09:41.206871 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:09:41.206892 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:09:41.206913 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:09:41.206939 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:09:41.206960 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:09:41.206982 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:09:41.207003 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:09:41.207023 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:09:41.207044 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:09:41.207065 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:09:41.207093 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.48232 (* 0.0454545 = 0.158287 loss) | |
| I0407 16:09:41.207124 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.5852 (* 0.0454545 = 0.162964 loss) | |
| I0407 16:09:41.207152 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.7465 (* 0.0454545 = 0.170296 loss) | |
| I0407 16:09:41.207180 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.88831 (* 0.0454545 = 0.176741 loss) | |
| I0407 16:09:41.207206 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.91228 (* 0.0454545 = 0.177831 loss) | |
| I0407 16:09:41.207231 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.69577 (* 0.0454545 = 0.122535 loss) | |
| I0407 16:09:41.207257 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.51086 (* 0.0454545 = 0.0686754 loss) | |
| I0407 16:09:41.207283 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.753717 (* 0.0454545 = 0.0342599 loss) | |
| I0407 16:09:41.207310 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.420035 (* 0.0454545 = 0.0190925 loss) | |
| I0407 16:09:41.207357 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0038791 (* 0.0454545 = 0.000176323 loss) | |
| I0407 16:09:41.207386 1004 solver.cpp:245] Train net output #32: loss/loss11 = 2.64498e-06 (* 0.0454545 = 1.20226e-07 loss) | |
| I0407 16:09:41.207412 1004 solver.cpp:245] Train net output #33: loss/loss12 = 2.68223e-06 (* 0.0454545 = 1.21919e-07 loss) | |
| I0407 16:09:41.207439 1004 solver.cpp:245] Train net output #34: loss/loss13 = 2.64498e-06 (* 0.0454545 = 1.20226e-07 loss) | |
| I0407 16:09:41.207465 1004 solver.cpp:245] Train net output #35: loss/loss14 = 2.72693e-06 (* 0.0454545 = 1.23952e-07 loss) | |
| I0407 16:09:41.207491 1004 solver.cpp:245] Train net output #36: loss/loss15 = 2.85359e-06 (* 0.0454545 = 1.29709e-07 loss) | |
| I0407 16:09:41.207518 1004 solver.cpp:245] Train net output #37: loss/loss16 = 2.39165e-06 (* 0.0454545 = 1.08711e-07 loss) | |
| I0407 16:09:41.207546 1004 solver.cpp:245] Train net output #38: loss/loss17 = 2.45126e-06 (* 0.0454545 = 1.11421e-07 loss) | |
| I0407 16:09:41.207595 1004 solver.cpp:245] Train net output #39: loss/loss18 = 2.97281e-06 (* 0.0454545 = 1.35128e-07 loss) | |
| I0407 16:09:41.207628 1004 solver.cpp:245] Train net output #40: loss/loss19 = 2.50341e-06 (* 0.0454545 = 1.13791e-07 loss) | |
| I0407 16:09:41.207656 1004 solver.cpp:245] Train net output #41: loss/loss20 = 2.3693e-06 (* 0.0454545 = 1.07695e-07 loss) | |
| I0407 16:09:41.207682 1004 solver.cpp:245] Train net output #42: loss/loss21 = 2.86105e-06 (* 0.0454545 = 1.30048e-07 loss) | |
| I0407 16:09:41.207710 1004 solver.cpp:245] Train net output #43: loss/loss22 = 2.9281e-06 (* 0.0454545 = 1.33096e-07 loss) | |
| I0407 16:09:41.207731 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:09:41.207753 1004 solver.cpp:245] Train net output #45: total_confidence = 3.33471e-06 | |
| I0407 16:09:41.207777 1004 sgd_solver.cpp:106] Iteration 42000, lr = 0.000916 | |
| I0407 16:10:20.026932 1004 solver.cpp:229] Iteration 42500, loss = 1.05689 | |
| I0407 16:10:20.027055 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:10:20.027086 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:10:20.027110 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:10:20.027132 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 16:10:20.027154 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.4375 | |
| I0407 16:10:20.027179 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5 | |
| I0407 16:10:20.027204 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 16:10:20.027226 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:10:20.027248 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:10:20.027271 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:10:20.027292 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:10:20.027313 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:10:20.027354 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:10:20.027379 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:10:20.027400 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:10:20.027421 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:10:20.027442 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:10:20.027464 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:10:20.027487 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:10:20.027508 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:10:20.027529 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:10:20.027550 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:10:20.027580 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.53632 (* 0.0454545 = 0.160742 loss) | |
| I0407 16:10:20.027611 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.49338 (* 0.0454545 = 0.15879 loss) | |
| I0407 16:10:20.027638 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.66774 (* 0.0454545 = 0.166716 loss) | |
| I0407 16:10:20.027664 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.45895 (* 0.0454545 = 0.157225 loss) | |
| I0407 16:10:20.027691 1004 solver.cpp:245] Train net output #26: loss/loss05 = 2.7542 (* 0.0454545 = 0.125191 loss) | |
| I0407 16:10:20.027717 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.40378 (* 0.0454545 = 0.109263 loss) | |
| I0407 16:10:20.027743 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.39015 (* 0.0454545 = 0.0631886 loss) | |
| I0407 16:10:20.027768 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.398589 (* 0.0454545 = 0.0181177 loss) | |
| I0407 16:10:20.027796 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.340866 (* 0.0454545 = 0.0154939 loss) | |
| I0407 16:10:20.027822 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0239878 (* 0.0454545 = 0.00109035 loss) | |
| I0407 16:10:20.027848 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000231467 (* 0.0454545 = 1.05212e-05 loss) | |
| I0407 16:10:20.027875 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000226229 (* 0.0454545 = 1.02831e-05 loss) | |
| I0407 16:10:20.027901 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000231871 (* 0.0454545 = 1.05396e-05 loss) | |
| I0407 16:10:20.027931 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000235726 (* 0.0454545 = 1.07148e-05 loss) | |
| I0407 16:10:20.027959 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000266565 (* 0.0454545 = 1.21166e-05 loss) | |
| I0407 16:10:20.027987 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000215614 (* 0.0454545 = 9.80065e-06 loss) | |
| I0407 16:10:20.028013 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000233701 (* 0.0454545 = 1.06228e-05 loss) | |
| I0407 16:10:20.028062 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000241707 (* 0.0454545 = 1.09867e-05 loss) | |
| I0407 16:10:20.028095 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000214653 (* 0.0454545 = 9.75696e-06 loss) | |
| I0407 16:10:20.028123 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000210813 (* 0.0454545 = 9.58241e-06 loss) | |
| I0407 16:10:20.028149 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000250061 (* 0.0454545 = 1.13664e-05 loss) | |
| I0407 16:10:20.028177 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000270089 (* 0.0454545 = 1.22768e-05 loss) | |
| I0407 16:10:20.028198 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:10:20.028219 1004 solver.cpp:245] Train net output #45: total_confidence = 6.65449e-05 | |
| I0407 16:10:20.028242 1004 sgd_solver.cpp:106] Iteration 42500, lr = 0.000915 | |
| I0407 16:10:58.766822 1004 solver.cpp:229] Iteration 43000, loss = 1.0558 | |
| I0407 16:10:58.766976 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:10:58.766998 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:10:58.767010 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:10:58.767022 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 16:10:58.767035 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 16:10:58.767047 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5 | |
| I0407 16:10:58.767060 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 16:10:58.767071 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 16:10:58.767084 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:10:58.767096 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:10:58.767108 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:10:58.767120 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:10:58.767132 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:10:58.767149 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:10:58.767163 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:10:58.767174 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:10:58.767186 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:10:58.767199 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:10:58.767210 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:10:58.767221 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:10:58.767232 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:10:58.767244 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:10:58.767261 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.59235 (* 0.0454545 = 0.163289 loss) | |
| I0407 16:10:58.767276 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.54408 (* 0.0454545 = 0.161094 loss) | |
| I0407 16:10:58.767289 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.6483 (* 0.0454545 = 0.165832 loss) | |
| I0407 16:10:58.767304 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.45882 (* 0.0454545 = 0.157219 loss) | |
| I0407 16:10:58.767330 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.04205 (* 0.0454545 = 0.138275 loss) | |
| I0407 16:10:58.767348 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.16017 (* 0.0454545 = 0.0981897 loss) | |
| I0407 16:10:58.767362 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.75095 (* 0.0454545 = 0.0795885 loss) | |
| I0407 16:10:58.767380 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.827179 (* 0.0454545 = 0.0375991 loss) | |
| I0407 16:10:58.767395 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.423537 (* 0.0454545 = 0.0192517 loss) | |
| I0407 16:10:58.767410 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.00347628 (* 0.0454545 = 0.000158013 loss) | |
| I0407 16:10:58.767424 1004 solver.cpp:245] Train net output #32: loss/loss11 = 4.18729e-06 (* 0.0454545 = 1.90332e-07 loss) | |
| I0407 16:10:58.767439 1004 solver.cpp:245] Train net output #33: loss/loss12 = 4.17239e-06 (* 0.0454545 = 1.89654e-07 loss) | |
| I0407 16:10:58.767453 1004 solver.cpp:245] Train net output #34: loss/loss13 = 4.1873e-06 (* 0.0454545 = 1.90332e-07 loss) | |
| I0407 16:10:58.767468 1004 solver.cpp:245] Train net output #35: loss/loss14 = 4.07553e-06 (* 0.0454545 = 1.85251e-07 loss) | |
| I0407 16:10:58.767482 1004 solver.cpp:245] Train net output #36: loss/loss15 = 4.67905e-06 (* 0.0454545 = 2.12684e-07 loss) | |
| I0407 16:10:58.767496 1004 solver.cpp:245] Train net output #37: loss/loss16 = 3.78495e-06 (* 0.0454545 = 1.72043e-07 loss) | |
| I0407 16:10:58.767510 1004 solver.cpp:245] Train net output #38: loss/loss17 = 4.32141e-06 (* 0.0454545 = 1.96428e-07 loss) | |
| I0407 16:10:58.767539 1004 solver.cpp:245] Train net output #39: loss/loss18 = 4.44807e-06 (* 0.0454545 = 2.02185e-07 loss) | |
| I0407 16:10:58.767555 1004 solver.cpp:245] Train net output #40: loss/loss19 = 4.47043e-06 (* 0.0454545 = 2.03201e-07 loss) | |
| I0407 16:10:58.767570 1004 solver.cpp:245] Train net output #41: loss/loss20 = 4.16494e-06 (* 0.0454545 = 1.89316e-07 loss) | |
| I0407 16:10:58.767583 1004 solver.cpp:245] Train net output #42: loss/loss21 = 4.45552e-06 (* 0.0454545 = 2.02524e-07 loss) | |
| I0407 16:10:58.767597 1004 solver.cpp:245] Train net output #43: loss/loss22 = 4.35121e-06 (* 0.0454545 = 1.97782e-07 loss) | |
| I0407 16:10:58.767609 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:10:58.767621 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000192689 | |
| I0407 16:10:58.767635 1004 sgd_solver.cpp:106] Iteration 43000, lr = 0.000914 | |
| I0407 16:11:37.452505 1004 solver.cpp:229] Iteration 43500, loss = 1.05198 | |
| I0407 16:11:37.452620 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:11:37.452641 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:11:37.452654 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:11:37.452666 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.3125 | |
| I0407 16:11:37.452678 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 16:11:37.452690 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5 | |
| I0407 16:11:37.452702 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.875 | |
| I0407 16:11:37.452713 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:11:37.452725 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:11:37.452738 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:11:37.452749 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:11:37.452760 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:11:37.452772 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:11:37.452783 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:11:37.452795 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:11:37.452807 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:11:37.452818 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:11:37.452831 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:11:37.452841 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:11:37.452853 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:11:37.452865 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:11:37.452877 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:11:37.452893 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.37129 (* 0.0454545 = 0.15324 loss) | |
| I0407 16:11:37.452908 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.58186 (* 0.0454545 = 0.162812 loss) | |
| I0407 16:11:37.452924 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.74873 (* 0.0454545 = 0.170397 loss) | |
| I0407 16:11:37.452939 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.36071 (* 0.0454545 = 0.152759 loss) | |
| I0407 16:11:37.452952 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.51069 (* 0.0454545 = 0.159577 loss) | |
| I0407 16:11:37.452966 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.60938 (* 0.0454545 = 0.118608 loss) | |
| I0407 16:11:37.452980 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.02015 (* 0.0454545 = 0.0463706 loss) | |
| I0407 16:11:37.452994 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.500685 (* 0.0454545 = 0.0227584 loss) | |
| I0407 16:11:37.453008 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0649112 (* 0.0454545 = 0.00295051 loss) | |
| I0407 16:11:37.453022 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0273216 (* 0.0454545 = 0.00124189 loss) | |
| I0407 16:11:37.453037 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000215966 (* 0.0454545 = 9.81665e-06 loss) | |
| I0407 16:11:37.453052 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000204134 (* 0.0454545 = 9.27881e-06 loss) | |
| I0407 16:11:37.453065 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000218668 (* 0.0454545 = 9.93946e-06 loss) | |
| I0407 16:11:37.453079 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000218322 (* 0.0454545 = 9.92371e-06 loss) | |
| I0407 16:11:37.453094 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000224756 (* 0.0454545 = 1.02162e-05 loss) | |
| I0407 16:11:37.453107 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.0001913 (* 0.0454545 = 8.69543e-06 loss) | |
| I0407 16:11:37.453122 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000202475 (* 0.0454545 = 9.20341e-06 loss) | |
| I0407 16:11:37.453160 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000215676 (* 0.0454545 = 9.80345e-06 loss) | |
| I0407 16:11:37.453176 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000213365 (* 0.0454545 = 9.69842e-06 loss) | |
| I0407 16:11:37.453189 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000201688 (* 0.0454545 = 9.16765e-06 loss) | |
| I0407 16:11:37.453203 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000209018 (* 0.0454545 = 9.50083e-06 loss) | |
| I0407 16:11:37.453218 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000230077 (* 0.0454545 = 1.04581e-05 loss) | |
| I0407 16:11:37.453230 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:11:37.453241 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000213645 | |
| I0407 16:11:37.453255 1004 sgd_solver.cpp:106] Iteration 43500, lr = 0.000913 | |
| I0407 16:12:15.861529 1004 solver.cpp:229] Iteration 44000, loss = 1.04971 | |
| I0407 16:12:15.861632 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:12:15.861652 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:12:15.861665 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:12:15.861677 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 16:12:15.861690 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 16:12:15.861702 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.1875 | |
| I0407 16:12:15.861713 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.625 | |
| I0407 16:12:15.861726 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 16:12:15.861738 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:12:15.861750 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:12:15.861762 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:12:15.861776 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:12:15.861789 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:12:15.861800 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:12:15.861812 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:12:15.861824 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:12:15.861835 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:12:15.861846 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:12:15.861858 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:12:15.861870 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:12:15.861881 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:12:15.861892 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:12:15.861908 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.79473 (* 0.0454545 = 0.172488 loss) | |
| I0407 16:12:15.861922 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.35585 (* 0.0454545 = 0.152538 loss) | |
| I0407 16:12:15.861937 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.31104 (* 0.0454545 = 0.150502 loss) | |
| I0407 16:12:15.861951 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.36448 (* 0.0454545 = 0.152931 loss) | |
| I0407 16:12:15.861965 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.64479 (* 0.0454545 = 0.165672 loss) | |
| I0407 16:12:15.861979 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.9092 (* 0.0454545 = 0.177691 loss) | |
| I0407 16:12:15.861994 1004 solver.cpp:245] Train net output #28: loss/loss07 = 2.36703 (* 0.0454545 = 0.107592 loss) | |
| I0407 16:12:15.862007 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.897398 (* 0.0454545 = 0.0407908 loss) | |
| I0407 16:12:15.862022 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0133532 (* 0.0454545 = 0.000606966 loss) | |
| I0407 16:12:15.862036 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.00356786 (* 0.0454545 = 0.000162175 loss) | |
| I0407 16:12:15.862051 1004 solver.cpp:245] Train net output #32: loss/loss11 = 3.76263e-06 (* 0.0454545 = 1.71029e-07 loss) | |
| I0407 16:12:15.862066 1004 solver.cpp:245] Train net output #33: loss/loss12 = 4.45557e-06 (* 0.0454545 = 2.02526e-07 loss) | |
| I0407 16:12:15.862082 1004 solver.cpp:245] Train net output #34: loss/loss13 = 4.00106e-06 (* 0.0454545 = 1.81866e-07 loss) | |
| I0407 16:12:15.862097 1004 solver.cpp:245] Train net output #35: loss/loss14 = 3.97126e-06 (* 0.0454545 = 1.80512e-07 loss) | |
| I0407 16:12:15.862110 1004 solver.cpp:245] Train net output #36: loss/loss15 = 4.05322e-06 (* 0.0454545 = 1.84237e-07 loss) | |
| I0407 16:12:15.862125 1004 solver.cpp:245] Train net output #37: loss/loss16 = 3.70302e-06 (* 0.0454545 = 1.68319e-07 loss) | |
| I0407 16:12:15.862138 1004 solver.cpp:245] Train net output #38: loss/loss17 = 3.79243e-06 (* 0.0454545 = 1.72383e-07 loss) | |
| I0407 16:12:15.862169 1004 solver.cpp:245] Train net output #39: loss/loss18 = 4.40341e-06 (* 0.0454545 = 2.00155e-07 loss) | |
| I0407 16:12:15.862185 1004 solver.cpp:245] Train net output #40: loss/loss19 = 3.92655e-06 (* 0.0454545 = 1.7848e-07 loss) | |
| I0407 16:12:15.862200 1004 solver.cpp:245] Train net output #41: loss/loss20 = 3.58381e-06 (* 0.0454545 = 1.629e-07 loss) | |
| I0407 16:12:15.862228 1004 solver.cpp:245] Train net output #42: loss/loss21 = 3.61361e-06 (* 0.0454545 = 1.64255e-07 loss) | |
| I0407 16:12:15.862251 1004 solver.cpp:245] Train net output #43: loss/loss22 = 3.71792e-06 (* 0.0454545 = 1.68996e-07 loss) | |
| I0407 16:12:15.862263 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:12:15.862274 1004 solver.cpp:245] Train net output #45: total_confidence = 0.00131379 | |
| I0407 16:12:15.862288 1004 sgd_solver.cpp:106] Iteration 44000, lr = 0.000912 | |
| I0407 16:12:54.354609 1004 solver.cpp:229] Iteration 44500, loss = 1.05391 | |
| I0407 16:12:54.354727 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:12:54.354756 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:12:54.354780 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:12:54.354802 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 16:12:54.354825 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 16:12:54.354854 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 16:12:54.354882 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.875 | |
| I0407 16:12:54.354903 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:12:54.354926 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:12:54.354948 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:12:54.354969 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:12:54.354991 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:12:54.355012 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:12:54.355033 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:12:54.355054 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:12:54.355078 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:12:54.355100 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:12:54.355123 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:12:54.355144 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:12:54.355165 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:12:54.355186 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:12:54.355208 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:12:54.355237 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.25898 (* 0.0454545 = 0.148135 loss) | |
| I0407 16:12:54.355265 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.5851 (* 0.0454545 = 0.162959 loss) | |
| I0407 16:12:54.355290 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.52586 (* 0.0454545 = 0.160266 loss) | |
| I0407 16:12:54.355334 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.47658 (* 0.0454545 = 0.158026 loss) | |
| I0407 16:12:54.355365 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.15968 (* 0.0454545 = 0.143622 loss) | |
| I0407 16:12:54.355392 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.81803 (* 0.0454545 = 0.128092 loss) | |
| I0407 16:12:54.355418 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.836975 (* 0.0454545 = 0.0380443 loss) | |
| I0407 16:12:54.355443 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.368638 (* 0.0454545 = 0.0167563 loss) | |
| I0407 16:12:54.355470 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.46782 (* 0.0454545 = 0.0212646 loss) | |
| I0407 16:12:54.355496 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.00960963 (* 0.0454545 = 0.000436801 loss) | |
| I0407 16:12:54.355522 1004 solver.cpp:245] Train net output #32: loss/loss11 = 1.05876e-05 (* 0.0454545 = 4.81253e-07 loss) | |
| I0407 16:12:54.355551 1004 solver.cpp:245] Train net output #33: loss/loss12 = 1.17201e-05 (* 0.0454545 = 5.32733e-07 loss) | |
| I0407 16:12:54.355577 1004 solver.cpp:245] Train net output #34: loss/loss13 = 1.11837e-05 (* 0.0454545 = 5.08348e-07 loss) | |
| I0407 16:12:54.355603 1004 solver.cpp:245] Train net output #35: loss/loss14 = 1.14072e-05 (* 0.0454545 = 5.18508e-07 loss) | |
| I0407 16:12:54.355629 1004 solver.cpp:245] Train net output #36: loss/loss15 = 1.15636e-05 (* 0.0454545 = 5.2562e-07 loss) | |
| I0407 16:12:54.355655 1004 solver.cpp:245] Train net output #37: loss/loss16 = 1.06993e-05 (* 0.0454545 = 4.86332e-07 loss) | |
| I0407 16:12:54.355681 1004 solver.cpp:245] Train net output #38: loss/loss17 = 1.08036e-05 (* 0.0454545 = 4.91075e-07 loss) | |
| I0407 16:12:54.355731 1004 solver.cpp:245] Train net output #39: loss/loss18 = 1.15264e-05 (* 0.0454545 = 5.23927e-07 loss) | |
| I0407 16:12:54.355759 1004 solver.cpp:245] Train net output #40: loss/loss19 = 1.07589e-05 (* 0.0454545 = 4.89042e-07 loss) | |
| I0407 16:12:54.355787 1004 solver.cpp:245] Train net output #41: loss/loss20 = 1.11389e-05 (* 0.0454545 = 5.06316e-07 loss) | |
| I0407 16:12:54.355813 1004 solver.cpp:245] Train net output #42: loss/loss21 = 1.17127e-05 (* 0.0454545 = 5.32394e-07 loss) | |
| I0407 16:12:54.355839 1004 solver.cpp:245] Train net output #43: loss/loss22 = 1.18319e-05 (* 0.0454545 = 5.37813e-07 loss) | |
| I0407 16:12:54.355860 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:12:54.355882 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000123098 | |
| I0407 16:12:54.355911 1004 sgd_solver.cpp:106] Iteration 44500, lr = 0.000911 | |
| I0407 16:13:32.844895 1004 solver.cpp:338] Iteration 45000, Testing net (#0) | |
| I0407 16:13:40.818805 1004 solver.cpp:393] Test loss: 0.96219 | |
| I0407 16:13:40.818852 1004 solver.cpp:406] Test net output #0: loss/accuracy01 = 0.311 | |
| I0407 16:13:40.818868 1004 solver.cpp:406] Test net output #1: loss/accuracy02 = 0.064 | |
| I0407 16:13:40.818881 1004 solver.cpp:406] Test net output #2: loss/accuracy03 = 0.065 | |
| I0407 16:13:40.818893 1004 solver.cpp:406] Test net output #3: loss/accuracy04 = 0.077 | |
| I0407 16:13:40.818907 1004 solver.cpp:406] Test net output #4: loss/accuracy05 = 0.203 | |
| I0407 16:13:40.818920 1004 solver.cpp:406] Test net output #5: loss/accuracy06 = 0.501 | |
| I0407 16:13:40.818933 1004 solver.cpp:406] Test net output #6: loss/accuracy07 = 0.894 | |
| I0407 16:13:40.818944 1004 solver.cpp:406] Test net output #7: loss/accuracy08 = 0.97 | |
| I0407 16:13:40.818956 1004 solver.cpp:406] Test net output #8: loss/accuracy09 = 0.995 | |
| I0407 16:13:40.818967 1004 solver.cpp:406] Test net output #9: loss/accuracy10 = 0.998 | |
| I0407 16:13:40.818979 1004 solver.cpp:406] Test net output #10: loss/accuracy11 = 1 | |
| I0407 16:13:40.818990 1004 solver.cpp:406] Test net output #11: loss/accuracy12 = 1 | |
| I0407 16:13:40.819001 1004 solver.cpp:406] Test net output #12: loss/accuracy13 = 1 | |
| I0407 16:13:40.819011 1004 solver.cpp:406] Test net output #13: loss/accuracy14 = 1 | |
| I0407 16:13:40.819023 1004 solver.cpp:406] Test net output #14: loss/accuracy15 = 1 | |
| I0407 16:13:40.819034 1004 solver.cpp:406] Test net output #15: loss/accuracy16 = 1 | |
| I0407 16:13:40.819046 1004 solver.cpp:406] Test net output #16: loss/accuracy17 = 1 | |
| I0407 16:13:40.819057 1004 solver.cpp:406] Test net output #17: loss/accuracy18 = 1 | |
| I0407 16:13:40.819069 1004 solver.cpp:406] Test net output #18: loss/accuracy19 = 1 | |
| I0407 16:13:40.819080 1004 solver.cpp:406] Test net output #19: loss/accuracy20 = 1 | |
| I0407 16:13:40.819092 1004 solver.cpp:406] Test net output #20: loss/accuracy21 = 1 | |
| I0407 16:13:40.819103 1004 solver.cpp:406] Test net output #21: loss/accuracy22 = 1 | |
| I0407 16:13:40.819118 1004 solver.cpp:406] Test net output #22: loss/loss01 = 3.32963 (* 0.0454545 = 0.151347 loss) | |
| I0407 16:13:40.819133 1004 solver.cpp:406] Test net output #23: loss/loss02 = 3.48268 (* 0.0454545 = 0.158304 loss) | |
| I0407 16:13:40.819145 1004 solver.cpp:406] Test net output #24: loss/loss03 = 3.57628 (* 0.0454545 = 0.162558 loss) | |
| I0407 16:13:40.819159 1004 solver.cpp:406] Test net output #25: loss/loss04 = 3.49714 (* 0.0454545 = 0.158961 loss) | |
| I0407 16:13:40.819172 1004 solver.cpp:406] Test net output #26: loss/loss05 = 3.36077 (* 0.0454545 = 0.152762 loss) | |
| I0407 16:13:40.819185 1004 solver.cpp:406] Test net output #27: loss/loss06 = 2.50469 (* 0.0454545 = 0.113849 loss) | |
| I0407 16:13:40.819200 1004 solver.cpp:406] Test net output #28: loss/loss07 = 0.860732 (* 0.0454545 = 0.0391242 loss) | |
| I0407 16:13:40.819212 1004 solver.cpp:406] Test net output #29: loss/loss08 = 0.334538 (* 0.0454545 = 0.0152063 loss) | |
| I0407 16:13:40.819226 1004 solver.cpp:406] Test net output #30: loss/loss09 = 0.0986105 (* 0.0454545 = 0.0044823 loss) | |
| I0407 16:13:40.819241 1004 solver.cpp:406] Test net output #31: loss/loss10 = 0.0449599 (* 0.0454545 = 0.00204363 loss) | |
| I0407 16:13:40.819254 1004 solver.cpp:406] Test net output #32: loss/loss11 = 0.00650921 (* 0.0454545 = 0.000295873 loss) | |
| I0407 16:13:40.819267 1004 solver.cpp:406] Test net output #33: loss/loss12 = 0.00656411 (* 0.0454545 = 0.000298369 loss) | |
| I0407 16:13:40.819281 1004 solver.cpp:406] Test net output #34: loss/loss13 = 0.0065198 (* 0.0454545 = 0.000296355 loss) | |
| I0407 16:13:40.819295 1004 solver.cpp:406] Test net output #35: loss/loss14 = 0.00648324 (* 0.0454545 = 0.000294693 loss) | |
| I0407 16:13:40.819309 1004 solver.cpp:406] Test net output #36: loss/loss15 = 0.00651071 (* 0.0454545 = 0.000295941 loss) | |
| I0407 16:13:40.819344 1004 solver.cpp:406] Test net output #37: loss/loss16 = 0.00652626 (* 0.0454545 = 0.000296648 loss) | |
| I0407 16:13:40.819360 1004 solver.cpp:406] Test net output #38: loss/loss17 = 0.00653023 (* 0.0454545 = 0.000296829 loss) | |
| I0407 16:13:40.819411 1004 solver.cpp:406] Test net output #39: loss/loss18 = 0.00648682 (* 0.0454545 = 0.000294855 loss) | |
| I0407 16:13:40.819425 1004 solver.cpp:406] Test net output #40: loss/loss19 = 0.00652397 (* 0.0454545 = 0.000296544 loss) | |
| I0407 16:13:40.819439 1004 solver.cpp:406] Test net output #41: loss/loss20 = 0.00654242 (* 0.0454545 = 0.000297383 loss) | |
| I0407 16:13:40.819453 1004 solver.cpp:406] Test net output #42: loss/loss21 = 0.00644227 (* 0.0454545 = 0.00029283 loss) | |
| I0407 16:13:40.819466 1004 solver.cpp:406] Test net output #43: loss/loss22 = 0.00650584 (* 0.0454545 = 0.00029572 loss) | |
| I0407 16:13:40.819479 1004 solver.cpp:406] Test net output #44: total_accuracy = 0 | |
| I0407 16:13:40.819490 1004 solver.cpp:406] Test net output #45: total_confidence = 0.000368678 | |
| I0407 16:13:40.841508 1004 solver.cpp:229] Iteration 45000, loss = 1.04826 | |
| I0407 16:13:40.841547 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.1875 | |
| I0407 16:13:40.841563 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:13:40.841575 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.25 | |
| I0407 16:13:40.841588 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 16:13:40.841599 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.3125 | |
| I0407 16:13:40.841611 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5625 | |
| I0407 16:13:40.841624 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.9375 | |
| I0407 16:13:40.841634 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 16:13:40.841648 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:13:40.841660 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:13:40.841671 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:13:40.841682 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:13:40.841693 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:13:40.841706 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:13:40.841717 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:13:40.841727 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:13:40.841739 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:13:40.841750 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:13:40.841763 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:13:40.841773 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:13:40.841784 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:13:40.841796 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:13:40.841810 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.013 (* 0.0454545 = 0.136955 loss) | |
| I0407 16:13:40.841825 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.27994 (* 0.0454545 = 0.149088 loss) | |
| I0407 16:13:40.841838 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.12054 (* 0.0454545 = 0.141843 loss) | |
| I0407 16:13:40.841852 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.75047 (* 0.0454545 = 0.170476 loss) | |
| I0407 16:13:40.841866 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.12201 (* 0.0454545 = 0.141909 loss) | |
| I0407 16:13:40.841881 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.11648 (* 0.0454545 = 0.0962035 loss) | |
| I0407 16:13:40.841894 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.46768 (* 0.0454545 = 0.0212582 loss) | |
| I0407 16:13:40.841908 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.109696 (* 0.0454545 = 0.00498616 loss) | |
| I0407 16:13:40.841922 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0542078 (* 0.0454545 = 0.00246399 loss) | |
| I0407 16:13:40.841935 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0230335 (* 0.0454545 = 0.00104698 loss) | |
| I0407 16:13:40.841967 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000386686 (* 0.0454545 = 1.75767e-05 loss) | |
| I0407 16:13:40.841984 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000385696 (* 0.0454545 = 1.75316e-05 loss) | |
| I0407 16:13:40.841997 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000412886 (* 0.0454545 = 1.87676e-05 loss) | |
| I0407 16:13:40.842011 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000416869 (* 0.0454545 = 1.89486e-05 loss) | |
| I0407 16:13:40.842025 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000424392 (* 0.0454545 = 1.92906e-05 loss) | |
| I0407 16:13:40.842039 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000411958 (* 0.0454545 = 1.87254e-05 loss) | |
| I0407 16:13:40.842053 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000422924 (* 0.0454545 = 1.92238e-05 loss) | |
| I0407 16:13:40.842067 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000414799 (* 0.0454545 = 1.88545e-05 loss) | |
| I0407 16:13:40.842084 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.0004018 (* 0.0454545 = 1.82636e-05 loss) | |
| I0407 16:13:40.842098 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000412835 (* 0.0454545 = 1.87652e-05 loss) | |
| I0407 16:13:40.842113 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00043625 (* 0.0454545 = 1.98295e-05 loss) | |
| I0407 16:13:40.842126 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00041586 (* 0.0454545 = 1.89027e-05 loss) | |
| I0407 16:13:40.842139 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:13:40.842150 1004 solver.cpp:245] Train net output #45: total_confidence = 0.00180509 | |
| I0407 16:13:40.842164 1004 sgd_solver.cpp:106] Iteration 45000, lr = 0.00091 | |
| I0407 16:14:19.346454 1004 solver.cpp:229] Iteration 45500, loss = 1.04534 | |
| I0407 16:14:19.346566 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 16:14:19.346585 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.125 | |
| I0407 16:14:19.346599 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:14:19.346611 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 16:14:19.346623 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 16:14:19.346637 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 16:14:19.346648 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 16:14:19.346660 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:14:19.346673 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:14:19.346684 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:14:19.346696 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:14:19.346707 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:14:19.346719 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:14:19.346730 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:14:19.346742 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:14:19.346753 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:14:19.346765 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:14:19.346776 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:14:19.346788 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:14:19.346799 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:14:19.346812 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:14:19.346822 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:14:19.346838 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.44922 (* 0.0454545 = 0.156783 loss) | |
| I0407 16:14:19.346853 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.69372 (* 0.0454545 = 0.167896 loss) | |
| I0407 16:14:19.346866 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.89888 (* 0.0454545 = 0.177222 loss) | |
| I0407 16:14:19.346880 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.79714 (* 0.0454545 = 0.172597 loss) | |
| I0407 16:14:19.346894 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.82146 (* 0.0454545 = 0.173703 loss) | |
| I0407 16:14:19.346909 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.71882 (* 0.0454545 = 0.123583 loss) | |
| I0407 16:14:19.346925 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.31962 (* 0.0454545 = 0.0599828 loss) | |
| I0407 16:14:19.346940 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.482372 (* 0.0454545 = 0.021926 loss) | |
| I0407 16:14:19.346953 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.458346 (* 0.0454545 = 0.0208339 loss) | |
| I0407 16:14:19.346967 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0316026 (* 0.0454545 = 0.00143648 loss) | |
| I0407 16:14:19.346982 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.00129568 (* 0.0454545 = 5.88946e-05 loss) | |
| I0407 16:14:19.346997 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00138562 (* 0.0454545 = 6.29828e-05 loss) | |
| I0407 16:14:19.347010 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.00120512 (* 0.0454545 = 5.4778e-05 loss) | |
| I0407 16:14:19.347024 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00121076 (* 0.0454545 = 5.50347e-05 loss) | |
| I0407 16:14:19.347038 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.001344 (* 0.0454545 = 6.10911e-05 loss) | |
| I0407 16:14:19.347054 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.0012626 (* 0.0454545 = 5.73909e-05 loss) | |
| I0407 16:14:19.347067 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.00120187 (* 0.0454545 = 5.46303e-05 loss) | |
| I0407 16:14:19.347097 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.00128776 (* 0.0454545 = 5.85346e-05 loss) | |
| I0407 16:14:19.347113 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00119389 (* 0.0454545 = 5.42678e-05 loss) | |
| I0407 16:14:19.347127 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.00119433 (* 0.0454545 = 5.42879e-05 loss) | |
| I0407 16:14:19.347141 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00127727 (* 0.0454545 = 5.80577e-05 loss) | |
| I0407 16:14:19.347156 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00133792 (* 0.0454545 = 6.08144e-05 loss) | |
| I0407 16:14:19.347167 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:14:19.347178 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000816305 | |
| I0407 16:14:19.347193 1004 sgd_solver.cpp:106] Iteration 45500, lr = 0.000909 | |
| I0407 16:14:57.884943 1004 solver.cpp:229] Iteration 46000, loss = 1.03642 | |
| I0407 16:14:57.885097 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:14:57.885116 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:14:57.885129 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:14:57.885141 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 16:14:57.885154 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 16:14:57.885166 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 16:14:57.885179 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 16:14:57.885190 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 16:14:57.885202 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:14:57.885213 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:14:57.885226 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:14:57.885236 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:14:57.885248 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:14:57.885259 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:14:57.885272 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:14:57.885283 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:14:57.885294 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:14:57.885306 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:14:57.885318 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:14:57.885329 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:14:57.885341 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:14:57.885352 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:14:57.885368 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.58438 (* 0.0454545 = 0.162926 loss) | |
| I0407 16:14:57.885382 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.95818 (* 0.0454545 = 0.179917 loss) | |
| I0407 16:14:57.885396 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.74015 (* 0.0454545 = 0.170007 loss) | |
| I0407 16:14:57.885411 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.55891 (* 0.0454545 = 0.161769 loss) | |
| I0407 16:14:57.885423 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.52532 (* 0.0454545 = 0.160242 loss) | |
| I0407 16:14:57.885437 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.90512 (* 0.0454545 = 0.132051 loss) | |
| I0407 16:14:57.885452 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.80332 (* 0.0454545 = 0.0819693 loss) | |
| I0407 16:14:57.885465 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.860128 (* 0.0454545 = 0.0390967 loss) | |
| I0407 16:14:57.885479 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.40378 (* 0.0454545 = 0.0183536 loss) | |
| I0407 16:14:57.885493 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.034325 (* 0.0454545 = 0.00156023 loss) | |
| I0407 16:14:57.885507 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000266734 (* 0.0454545 = 1.21243e-05 loss) | |
| I0407 16:14:57.885521 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000254395 (* 0.0454545 = 1.15634e-05 loss) | |
| I0407 16:14:57.885535 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000263443 (* 0.0454545 = 1.19747e-05 loss) | |
| I0407 16:14:57.885550 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000272219 (* 0.0454545 = 1.23736e-05 loss) | |
| I0407 16:14:57.885563 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000288056 (* 0.0454545 = 1.30935e-05 loss) | |
| I0407 16:14:57.885576 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000245642 (* 0.0454545 = 1.11656e-05 loss) | |
| I0407 16:14:57.885591 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000256855 (* 0.0454545 = 1.16752e-05 loss) | |
| I0407 16:14:57.885620 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000296659 (* 0.0454545 = 1.34845e-05 loss) | |
| I0407 16:14:57.885635 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000252572 (* 0.0454545 = 1.14805e-05 loss) | |
| I0407 16:14:57.885649 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000266709 (* 0.0454545 = 1.21231e-05 loss) | |
| I0407 16:14:57.885663 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000293885 (* 0.0454545 = 1.33584e-05 loss) | |
| I0407 16:14:57.885678 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000308697 (* 0.0454545 = 1.40317e-05 loss) | |
| I0407 16:14:57.885689 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:14:57.885701 1004 solver.cpp:245] Train net output #45: total_confidence = 2.27196e-06 | |
| I0407 16:14:57.885715 1004 sgd_solver.cpp:106] Iteration 46000, lr = 0.000908 | |
| I0407 16:15:36.458904 1004 solver.cpp:229] Iteration 46500, loss = 1.04441 | |
| I0407 16:15:36.459028 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:15:36.459048 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:15:36.459060 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:15:36.459072 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 16:15:36.459085 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.375 | |
| I0407 16:15:36.459098 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5625 | |
| I0407 16:15:36.459111 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 16:15:36.459122 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:15:36.459134 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:15:36.459146 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:15:36.459157 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:15:36.459169 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:15:36.459180 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:15:36.459192 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:15:36.459203 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:15:36.459214 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:15:36.459226 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:15:36.459238 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:15:36.459249 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:15:36.459261 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:15:36.459272 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:15:36.459283 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:15:36.459298 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.38198 (* 0.0454545 = 0.153726 loss) | |
| I0407 16:15:36.459313 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.73722 (* 0.0454545 = 0.169874 loss) | |
| I0407 16:15:36.459342 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.62712 (* 0.0454545 = 0.164869 loss) | |
| I0407 16:15:36.459357 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.54979 (* 0.0454545 = 0.161354 loss) | |
| I0407 16:15:36.459372 1004 solver.cpp:245] Train net output #26: loss/loss05 = 2.8725 (* 0.0454545 = 0.130568 loss) | |
| I0407 16:15:36.459385 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.15678 (* 0.0454545 = 0.0980353 loss) | |
| I0407 16:15:36.459399 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.994905 (* 0.0454545 = 0.0452229 loss) | |
| I0407 16:15:36.459413 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.372335 (* 0.0454545 = 0.0169243 loss) | |
| I0407 16:15:36.459427 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0297002 (* 0.0454545 = 0.00135001 loss) | |
| I0407 16:15:36.459441 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0115968 (* 0.0454545 = 0.000527128 loss) | |
| I0407 16:15:36.459455 1004 solver.cpp:245] Train net output #32: loss/loss11 = 3.60448e-05 (* 0.0454545 = 1.6384e-06 loss) | |
| I0407 16:15:36.459470 1004 solver.cpp:245] Train net output #33: loss/loss12 = 3.28777e-05 (* 0.0454545 = 1.49444e-06 loss) | |
| I0407 16:15:36.459484 1004 solver.cpp:245] Train net output #34: loss/loss13 = 3.38092e-05 (* 0.0454545 = 1.53678e-06 loss) | |
| I0407 16:15:36.459498 1004 solver.cpp:245] Train net output #35: loss/loss14 = 3.78704e-05 (* 0.0454545 = 1.72138e-06 loss) | |
| I0407 16:15:36.459512 1004 solver.cpp:245] Train net output #36: loss/loss15 = 4.01693e-05 (* 0.0454545 = 1.82588e-06 loss) | |
| I0407 16:15:36.459527 1004 solver.cpp:245] Train net output #37: loss/loss16 = 3.24456e-05 (* 0.0454545 = 1.4748e-06 loss) | |
| I0407 16:15:36.459542 1004 solver.cpp:245] Train net output #38: loss/loss17 = 3.69911e-05 (* 0.0454545 = 1.68141e-06 loss) | |
| I0407 16:15:36.459573 1004 solver.cpp:245] Train net output #39: loss/loss18 = 4.07841e-05 (* 0.0454545 = 1.85382e-06 loss) | |
| I0407 16:15:36.459589 1004 solver.cpp:245] Train net output #40: loss/loss19 = 3.29598e-05 (* 0.0454545 = 1.49817e-06 loss) | |
| I0407 16:15:36.459602 1004 solver.cpp:245] Train net output #41: loss/loss20 = 3.39136e-05 (* 0.0454545 = 1.54153e-06 loss) | |
| I0407 16:15:36.459616 1004 solver.cpp:245] Train net output #42: loss/loss21 = 3.89658e-05 (* 0.0454545 = 1.77117e-06 loss) | |
| I0407 16:15:36.459630 1004 solver.cpp:245] Train net output #43: loss/loss22 = 3.90626e-05 (* 0.0454545 = 1.77557e-06 loss) | |
| I0407 16:15:36.459642 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:15:36.459655 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000172716 | |
| I0407 16:15:36.459667 1004 sgd_solver.cpp:106] Iteration 46500, lr = 0.000907 | |
| I0407 16:16:15.830869 1004 solver.cpp:229] Iteration 47000, loss = 1.03534 | |
| I0407 16:16:15.831042 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 16:16:15.831061 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.125 | |
| I0407 16:16:15.831075 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:16:15.831087 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.25 | |
| I0407 16:16:15.831099 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 16:16:15.831111 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 16:16:15.831122 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 16:16:15.831135 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.75 | |
| I0407 16:16:15.831146 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:16:15.831158 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 16:16:15.831171 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:16:15.831182 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:16:15.831193 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:16:15.831204 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:16:15.831215 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:16:15.831228 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:16:15.831238 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:16:15.831250 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:16:15.831261 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:16:15.831274 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:16:15.831284 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:16:15.831295 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:16:15.831311 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.3712 (* 0.0454545 = 0.153236 loss) | |
| I0407 16:16:15.831341 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.41294 (* 0.0454545 = 0.155134 loss) | |
| I0407 16:16:15.831356 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.51058 (* 0.0454545 = 0.159572 loss) | |
| I0407 16:16:15.831369 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.33692 (* 0.0454545 = 0.151678 loss) | |
| I0407 16:16:15.831383 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.4817 (* 0.0454545 = 0.158259 loss) | |
| I0407 16:16:15.831396 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.86498 (* 0.0454545 = 0.130226 loss) | |
| I0407 16:16:15.831410 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.72454 (* 0.0454545 = 0.0783883 loss) | |
| I0407 16:16:15.831424 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.40979 (* 0.0454545 = 0.0640814 loss) | |
| I0407 16:16:15.831439 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.387482 (* 0.0454545 = 0.0176128 loss) | |
| I0407 16:16:15.831454 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.40572 (* 0.0454545 = 0.0184418 loss) | |
| I0407 16:16:15.831467 1004 solver.cpp:245] Train net output #32: loss/loss11 = 7.18578e-05 (* 0.0454545 = 3.26627e-06 loss) | |
| I0407 16:16:15.831482 1004 solver.cpp:245] Train net output #33: loss/loss12 = 7.69073e-05 (* 0.0454545 = 3.49579e-06 loss) | |
| I0407 16:16:15.831496 1004 solver.cpp:245] Train net output #34: loss/loss13 = 7.40453e-05 (* 0.0454545 = 3.36569e-06 loss) | |
| I0407 16:16:15.831511 1004 solver.cpp:245] Train net output #35: loss/loss14 = 7.35827e-05 (* 0.0454545 = 3.34467e-06 loss) | |
| I0407 16:16:15.831524 1004 solver.cpp:245] Train net output #36: loss/loss15 = 7.41606e-05 (* 0.0454545 = 3.37094e-06 loss) | |
| I0407 16:16:15.831538 1004 solver.cpp:245] Train net output #37: loss/loss16 = 6.70915e-05 (* 0.0454545 = 3.04961e-06 loss) | |
| I0407 16:16:15.831552 1004 solver.cpp:245] Train net output #38: loss/loss17 = 7.2573e-05 (* 0.0454545 = 3.29877e-06 loss) | |
| I0407 16:16:15.831581 1004 solver.cpp:245] Train net output #39: loss/loss18 = 7.89229e-05 (* 0.0454545 = 3.58741e-06 loss) | |
| I0407 16:16:15.831596 1004 solver.cpp:245] Train net output #40: loss/loss19 = 7.34637e-05 (* 0.0454545 = 3.33926e-06 loss) | |
| I0407 16:16:15.831610 1004 solver.cpp:245] Train net output #41: loss/loss20 = 7.63708e-05 (* 0.0454545 = 3.4714e-06 loss) | |
| I0407 16:16:15.831624 1004 solver.cpp:245] Train net output #42: loss/loss21 = 7.09292e-05 (* 0.0454545 = 3.22406e-06 loss) | |
| I0407 16:16:15.831639 1004 solver.cpp:245] Train net output #43: loss/loss22 = 7.94372e-05 (* 0.0454545 = 3.61078e-06 loss) | |
| I0407 16:16:15.831650 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:16:15.831662 1004 solver.cpp:245] Train net output #45: total_confidence = 5.40445e-06 | |
| I0407 16:16:15.831676 1004 sgd_solver.cpp:106] Iteration 47000, lr = 0.000906 | |
| I0407 16:16:54.801522 1004 solver.cpp:229] Iteration 47500, loss = 1.02981 | |
| I0407 16:16:54.801656 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:16:54.801676 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:16:54.801689 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:16:54.801702 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 16:16:54.801717 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 16:16:54.801729 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5 | |
| I0407 16:16:54.801741 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 16:16:54.801753 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:16:54.801765 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:16:54.801777 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 16:16:54.801789 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:16:54.801800 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:16:54.801812 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:16:54.801825 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:16:54.801836 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:16:54.801847 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:16:54.801858 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:16:54.801870 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:16:54.801882 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:16:54.801893 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:16:54.801904 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:16:54.801916 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:16:54.801933 1004 solver.cpp:245] Train net output #22: loss/loss01 = 2.98059 (* 0.0454545 = 0.135481 loss) | |
| I0407 16:16:54.801947 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.7481 (* 0.0454545 = 0.170368 loss) | |
| I0407 16:16:54.801961 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.75707 (* 0.0454545 = 0.170776 loss) | |
| I0407 16:16:54.801975 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.42108 (* 0.0454545 = 0.155504 loss) | |
| I0407 16:16:54.801990 1004 solver.cpp:245] Train net output #26: loss/loss05 = 2.98945 (* 0.0454545 = 0.135884 loss) | |
| I0407 16:16:54.802003 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.10575 (* 0.0454545 = 0.0957159 loss) | |
| I0407 16:16:54.802016 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.0561 (* 0.0454545 = 0.0480044 loss) | |
| I0407 16:16:54.802031 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.347474 (* 0.0454545 = 0.0157943 loss) | |
| I0407 16:16:54.802045 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.297833 (* 0.0454545 = 0.0135379 loss) | |
| I0407 16:16:54.802059 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.377383 (* 0.0454545 = 0.0171538 loss) | |
| I0407 16:16:54.802073 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000156084 (* 0.0454545 = 7.09473e-06 loss) | |
| I0407 16:16:54.802088 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000158619 (* 0.0454545 = 7.20995e-06 loss) | |
| I0407 16:16:54.802103 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000166379 (* 0.0454545 = 7.56267e-06 loss) | |
| I0407 16:16:54.802116 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000188584 (* 0.0454545 = 8.57201e-06 loss) | |
| I0407 16:16:54.802134 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000185016 (* 0.0454545 = 8.40981e-06 loss) | |
| I0407 16:16:54.802148 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000143638 (* 0.0454545 = 6.529e-06 loss) | |
| I0407 16:16:54.802162 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000164362 (* 0.0454545 = 7.47101e-06 loss) | |
| I0407 16:16:54.802194 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000174272 (* 0.0454545 = 7.92146e-06 loss) | |
| I0407 16:16:54.802209 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000168768 (* 0.0454545 = 7.67126e-06 loss) | |
| I0407 16:16:54.802223 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000170509 (* 0.0454545 = 7.7504e-06 loss) | |
| I0407 16:16:54.802237 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000147237 (* 0.0454545 = 6.69261e-06 loss) | |
| I0407 16:16:54.802251 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000158298 (* 0.0454545 = 7.19537e-06 loss) | |
| I0407 16:16:54.802264 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:16:54.802275 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000292966 | |
| I0407 16:16:54.802289 1004 sgd_solver.cpp:106] Iteration 47500, lr = 0.000905 | |
| I0407 16:17:33.541465 1004 solver.cpp:229] Iteration 48000, loss = 1.03065 | |
| I0407 16:17:33.541594 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 16:17:33.541615 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:17:33.541628 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:17:33.541640 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 16:17:33.541652 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 16:17:33.541664 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 16:17:33.541676 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 16:17:33.541688 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:17:33.541700 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:17:33.541712 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:17:33.541723 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:17:33.541735 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:17:33.541748 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:17:33.541759 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:17:33.541770 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:17:33.541781 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:17:33.541793 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:17:33.541805 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:17:33.541816 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:17:33.541827 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:17:33.541838 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:17:33.541851 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:17:33.541865 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.40376 (* 0.0454545 = 0.154716 loss) | |
| I0407 16:17:33.541879 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.76615 (* 0.0454545 = 0.171189 loss) | |
| I0407 16:17:33.541893 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.78736 (* 0.0454545 = 0.172153 loss) | |
| I0407 16:17:33.541908 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.80967 (* 0.0454545 = 0.173167 loss) | |
| I0407 16:17:33.541924 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.2188 (* 0.0454545 = 0.146309 loss) | |
| I0407 16:17:33.541939 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.10437 (* 0.0454545 = 0.141108 loss) | |
| I0407 16:17:33.541952 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.3407 (* 0.0454545 = 0.0609409 loss) | |
| I0407 16:17:33.541966 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.565279 (* 0.0454545 = 0.0256945 loss) | |
| I0407 16:17:33.541980 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0508242 (* 0.0454545 = 0.00231019 loss) | |
| I0407 16:17:33.541995 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0173991 (* 0.0454545 = 0.00079087 loss) | |
| I0407 16:17:33.542009 1004 solver.cpp:245] Train net output #32: loss/loss11 = 8.77874e-05 (* 0.0454545 = 3.99034e-06 loss) | |
| I0407 16:17:33.542024 1004 solver.cpp:245] Train net output #33: loss/loss12 = 8.56607e-05 (* 0.0454545 = 3.89367e-06 loss) | |
| I0407 16:17:33.542038 1004 solver.cpp:245] Train net output #34: loss/loss13 = 8.51572e-05 (* 0.0454545 = 3.87078e-06 loss) | |
| I0407 16:17:33.542052 1004 solver.cpp:245] Train net output #35: loss/loss14 = 8.96052e-05 (* 0.0454545 = 4.07297e-06 loss) | |
| I0407 16:17:33.542067 1004 solver.cpp:245] Train net output #36: loss/loss15 = 9.08389e-05 (* 0.0454545 = 4.12904e-06 loss) | |
| I0407 16:17:33.542079 1004 solver.cpp:245] Train net output #37: loss/loss16 = 7.97091e-05 (* 0.0454545 = 3.62314e-06 loss) | |
| I0407 16:17:33.542093 1004 solver.cpp:245] Train net output #38: loss/loss17 = 8.46276e-05 (* 0.0454545 = 3.84671e-06 loss) | |
| I0407 16:17:33.542124 1004 solver.cpp:245] Train net output #39: loss/loss18 = 9.16689e-05 (* 0.0454545 = 4.16677e-06 loss) | |
| I0407 16:17:33.542138 1004 solver.cpp:245] Train net output #40: loss/loss19 = 8.6215e-05 (* 0.0454545 = 3.91887e-06 loss) | |
| I0407 16:17:33.542152 1004 solver.cpp:245] Train net output #41: loss/loss20 = 8.30402e-05 (* 0.0454545 = 3.77456e-06 loss) | |
| I0407 16:17:33.542166 1004 solver.cpp:245] Train net output #42: loss/loss21 = 8.24575e-05 (* 0.0454545 = 3.74807e-06 loss) | |
| I0407 16:17:33.542179 1004 solver.cpp:245] Train net output #43: loss/loss22 = 9.29553e-05 (* 0.0454545 = 4.22524e-06 loss) | |
| I0407 16:17:33.542191 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:17:33.542203 1004 solver.cpp:245] Train net output #45: total_confidence = 4.03025e-05 | |
| I0407 16:17:33.542217 1004 sgd_solver.cpp:106] Iteration 48000, lr = 0.000904 | |
| I0407 16:18:12.378597 1004 solver.cpp:229] Iteration 48500, loss = 1.02865 | |
| I0407 16:18:12.378713 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:18:12.378731 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.1875 | |
| I0407 16:18:12.378744 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:18:12.378757 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 16:18:12.378768 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 16:18:12.378780 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 16:18:12.378793 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 16:18:12.378804 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 16:18:12.378819 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:18:12.378831 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:18:12.378844 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:18:12.378855 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:18:12.378867 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:18:12.378878 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:18:12.378890 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:18:12.378902 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:18:12.378913 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:18:12.378926 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:18:12.378937 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:18:12.378948 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:18:12.378959 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:18:12.378970 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:18:12.378986 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.52885 (* 0.0454545 = 0.160402 loss) | |
| I0407 16:18:12.379001 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.40163 (* 0.0454545 = 0.154619 loss) | |
| I0407 16:18:12.379015 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.42899 (* 0.0454545 = 0.155863 loss) | |
| I0407 16:18:12.379029 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.53761 (* 0.0454545 = 0.160801 loss) | |
| I0407 16:18:12.379042 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.27597 (* 0.0454545 = 0.148908 loss) | |
| I0407 16:18:12.379056 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.64647 (* 0.0454545 = 0.120294 loss) | |
| I0407 16:18:12.379070 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.52024 (* 0.0454545 = 0.0691018 loss) | |
| I0407 16:18:12.379086 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.0723126 (* 0.0454545 = 0.00328694 loss) | |
| I0407 16:18:12.379101 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0264784 (* 0.0454545 = 0.00120357 loss) | |
| I0407 16:18:12.379115 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.010223 (* 0.0454545 = 0.000464681 loss) | |
| I0407 16:18:12.379129 1004 solver.cpp:245] Train net output #32: loss/loss11 = 6.83463e-05 (* 0.0454545 = 3.10665e-06 loss) | |
| I0407 16:18:12.379149 1004 solver.cpp:245] Train net output #33: loss/loss12 = 6.7221e-05 (* 0.0454545 = 3.0555e-06 loss) | |
| I0407 16:18:12.379179 1004 solver.cpp:245] Train net output #34: loss/loss13 = 6.80932e-05 (* 0.0454545 = 3.09515e-06 loss) | |
| I0407 16:18:12.379199 1004 solver.cpp:245] Train net output #35: loss/loss14 = 7.62585e-05 (* 0.0454545 = 3.4663e-06 loss) | |
| I0407 16:18:12.379214 1004 solver.cpp:245] Train net output #36: loss/loss15 = 7.35653e-05 (* 0.0454545 = 3.34388e-06 loss) | |
| I0407 16:18:12.379227 1004 solver.cpp:245] Train net output #37: loss/loss16 = 6.20385e-05 (* 0.0454545 = 2.81993e-06 loss) | |
| I0407 16:18:12.379241 1004 solver.cpp:245] Train net output #38: loss/loss17 = 6.66125e-05 (* 0.0454545 = 3.02784e-06 loss) | |
| I0407 16:18:12.379273 1004 solver.cpp:245] Train net output #39: loss/loss18 = 7.75578e-05 (* 0.0454545 = 3.52535e-06 loss) | |
| I0407 16:18:12.379288 1004 solver.cpp:245] Train net output #40: loss/loss19 = 6.96853e-05 (* 0.0454545 = 3.16751e-06 loss) | |
| I0407 16:18:12.379302 1004 solver.cpp:245] Train net output #41: loss/loss20 = 6.31637e-05 (* 0.0454545 = 2.87108e-06 loss) | |
| I0407 16:18:12.379329 1004 solver.cpp:245] Train net output #42: loss/loss21 = 6.53472e-05 (* 0.0454545 = 2.97033e-06 loss) | |
| I0407 16:18:12.379348 1004 solver.cpp:245] Train net output #43: loss/loss22 = 6.72279e-05 (* 0.0454545 = 3.05581e-06 loss) | |
| I0407 16:18:12.379360 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:18:12.379371 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000338612 | |
| I0407 16:18:12.379384 1004 sgd_solver.cpp:106] Iteration 48500, lr = 0.000903 | |
| I0407 16:18:51.066939 1004 solver.cpp:229] Iteration 49000, loss = 1.02587 | |
| I0407 16:18:51.067082 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 16:18:51.067102 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:18:51.067116 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:18:51.067127 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 16:18:51.067140 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.3125 | |
| I0407 16:18:51.067152 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 16:18:51.067165 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.5625 | |
| I0407 16:18:51.067178 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 16:18:51.067189 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:18:51.067201 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:18:51.067214 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:18:51.067224 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:18:51.067236 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:18:51.067247 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:18:51.067260 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:18:51.067271 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:18:51.067282 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:18:51.067294 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:18:51.067306 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:18:51.067334 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:18:51.067348 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:18:51.067360 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:18:51.067378 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.32137 (* 0.0454545 = 0.150972 loss) | |
| I0407 16:18:51.067392 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.40286 (* 0.0454545 = 0.154675 loss) | |
| I0407 16:18:51.067406 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.65194 (* 0.0454545 = 0.165997 loss) | |
| I0407 16:18:51.067420 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.47745 (* 0.0454545 = 0.158066 loss) | |
| I0407 16:18:51.067435 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.0298 (* 0.0454545 = 0.137718 loss) | |
| I0407 16:18:51.067448 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.73156 (* 0.0454545 = 0.124162 loss) | |
| I0407 16:18:51.067462 1004 solver.cpp:245] Train net output #28: loss/loss07 = 2.27792 (* 0.0454545 = 0.103542 loss) | |
| I0407 16:18:51.067476 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.16615 (* 0.0454545 = 0.053007 loss) | |
| I0407 16:18:51.067490 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.343677 (* 0.0454545 = 0.0156217 loss) | |
| I0407 16:18:51.067504 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0104423 (* 0.0454545 = 0.000474649 loss) | |
| I0407 16:18:51.067519 1004 solver.cpp:245] Train net output #32: loss/loss11 = 4.26546e-05 (* 0.0454545 = 1.93884e-06 loss) | |
| I0407 16:18:51.067533 1004 solver.cpp:245] Train net output #33: loss/loss12 = 3.89385e-05 (* 0.0454545 = 1.76993e-06 loss) | |
| I0407 16:18:51.067548 1004 solver.cpp:245] Train net output #34: loss/loss13 = 3.84471e-05 (* 0.0454545 = 1.74759e-06 loss) | |
| I0407 16:18:51.067561 1004 solver.cpp:245] Train net output #35: loss/loss14 = 4.64447e-05 (* 0.0454545 = 2.11112e-06 loss) | |
| I0407 16:18:51.067576 1004 solver.cpp:245] Train net output #36: loss/loss15 = 4.91844e-05 (* 0.0454545 = 2.23565e-06 loss) | |
| I0407 16:18:51.067590 1004 solver.cpp:245] Train net output #37: loss/loss16 = 4.26618e-05 (* 0.0454545 = 1.93917e-06 loss) | |
| I0407 16:18:51.067605 1004 solver.cpp:245] Train net output #38: loss/loss17 = 4.14845e-05 (* 0.0454545 = 1.88566e-06 loss) | |
| I0407 16:18:51.067633 1004 solver.cpp:245] Train net output #39: loss/loss18 = 4.86956e-05 (* 0.0454545 = 2.21344e-06 loss) | |
| I0407 16:18:51.067648 1004 solver.cpp:245] Train net output #40: loss/loss19 = 4.23712e-05 (* 0.0454545 = 1.92596e-06 loss) | |
| I0407 16:18:51.067662 1004 solver.cpp:245] Train net output #41: loss/loss20 = 4.03173e-05 (* 0.0454545 = 1.8326e-06 loss) | |
| I0407 16:18:51.067677 1004 solver.cpp:245] Train net output #42: loss/loss21 = 4.55879e-05 (* 0.0454545 = 2.07218e-06 loss) | |
| I0407 16:18:51.067690 1004 solver.cpp:245] Train net output #43: loss/loss22 = 4.54047e-05 (* 0.0454545 = 2.06385e-06 loss) | |
| I0407 16:18:51.067703 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:18:51.067714 1004 solver.cpp:245] Train net output #45: total_confidence = 3.23424e-05 | |
| I0407 16:18:51.067728 1004 sgd_solver.cpp:106] Iteration 49000, lr = 0.000902 | |
| I0407 16:19:29.791137 1004 solver.cpp:229] Iteration 49500, loss = 1.02685 | |
| I0407 16:19:29.791273 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:19:29.791292 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.1875 | |
| I0407 16:19:29.791306 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:19:29.791317 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 16:19:29.791331 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 16:19:29.791342 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5 | |
| I0407 16:19:29.791354 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 16:19:29.791366 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:19:29.791378 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:19:29.791390 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:19:29.791415 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:19:29.791427 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:19:29.791440 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:19:29.791450 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:19:29.791462 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:19:29.791474 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:19:29.791486 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:19:29.791497 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:19:29.791508 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:19:29.791520 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:19:29.791532 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:19:29.791543 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:19:29.791559 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.1969 (* 0.0454545 = 0.145314 loss) | |
| I0407 16:19:29.791574 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.62436 (* 0.0454545 = 0.164744 loss) | |
| I0407 16:19:29.791589 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.59027 (* 0.0454545 = 0.163194 loss) | |
| I0407 16:19:29.791601 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.69769 (* 0.0454545 = 0.168077 loss) | |
| I0407 16:19:29.791615 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.10283 (* 0.0454545 = 0.141038 loss) | |
| I0407 16:19:29.791630 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.36932 (* 0.0454545 = 0.107696 loss) | |
| I0407 16:19:29.791643 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.29128 (* 0.0454545 = 0.0586944 loss) | |
| I0407 16:19:29.791656 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.32682 (* 0.0454545 = 0.0148555 loss) | |
| I0407 16:19:29.791671 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0548415 (* 0.0454545 = 0.00249279 loss) | |
| I0407 16:19:29.791687 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0212078 (* 0.0454545 = 0.00096399 loss) | |
| I0407 16:19:29.791700 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000184481 (* 0.0454545 = 8.38549e-06 loss) | |
| I0407 16:19:29.791715 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000190006 (* 0.0454545 = 8.63665e-06 loss) | |
| I0407 16:19:29.791729 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000174897 (* 0.0454545 = 7.94985e-06 loss) | |
| I0407 16:19:29.791743 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000172644 (* 0.0454545 = 7.84746e-06 loss) | |
| I0407 16:19:29.791757 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.00017686 (* 0.0454545 = 8.03909e-06 loss) | |
| I0407 16:19:29.791771 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000163493 (* 0.0454545 = 7.43149e-06 loss) | |
| I0407 16:19:29.791785 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000162598 (* 0.0454545 = 7.3908e-06 loss) | |
| I0407 16:19:29.792011 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000167816 (* 0.0454545 = 7.62798e-06 loss) | |
| I0407 16:19:29.792028 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000172709 (* 0.0454545 = 7.85043e-06 loss) | |
| I0407 16:19:29.792039 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000167947 (* 0.0454545 = 7.63395e-06 loss) | |
| I0407 16:19:29.792048 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000156339 (* 0.0454545 = 7.10634e-06 loss) | |
| I0407 16:19:29.792058 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000166595 (* 0.0454545 = 7.57249e-06 loss) | |
| I0407 16:19:29.792065 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:19:29.792073 1004 solver.cpp:245] Train net output #45: total_confidence = 0.00016746 | |
| I0407 16:19:29.792081 1004 sgd_solver.cpp:106] Iteration 49500, lr = 0.000901 | |
| I0407 16:20:08.458269 1004 solver.cpp:338] Iteration 50000, Testing net (#0) | |
| I0407 16:20:16.413247 1004 solver.cpp:393] Test loss: 0.965833 | |
| I0407 16:20:16.413293 1004 solver.cpp:406] Test net output #0: loss/accuracy01 = 0.307 | |
| I0407 16:20:16.413310 1004 solver.cpp:406] Test net output #1: loss/accuracy02 = 0.095 | |
| I0407 16:20:16.413322 1004 solver.cpp:406] Test net output #2: loss/accuracy03 = 0.057 | |
| I0407 16:20:16.413334 1004 solver.cpp:406] Test net output #3: loss/accuracy04 = 0.086 | |
| I0407 16:20:16.413347 1004 solver.cpp:406] Test net output #4: loss/accuracy05 = 0.2 | |
| I0407 16:20:16.413358 1004 solver.cpp:406] Test net output #5: loss/accuracy06 = 0.495 | |
| I0407 16:20:16.413369 1004 solver.cpp:406] Test net output #6: loss/accuracy07 = 0.894 | |
| I0407 16:20:16.413381 1004 solver.cpp:406] Test net output #7: loss/accuracy08 = 0.97 | |
| I0407 16:20:16.413393 1004 solver.cpp:406] Test net output #8: loss/accuracy09 = 0.995 | |
| I0407 16:20:16.413403 1004 solver.cpp:406] Test net output #9: loss/accuracy10 = 0.998 | |
| I0407 16:20:16.413414 1004 solver.cpp:406] Test net output #10: loss/accuracy11 = 1 | |
| I0407 16:20:16.413426 1004 solver.cpp:406] Test net output #11: loss/accuracy12 = 1 | |
| I0407 16:20:16.413437 1004 solver.cpp:406] Test net output #12: loss/accuracy13 = 1 | |
| I0407 16:20:16.413449 1004 solver.cpp:406] Test net output #13: loss/accuracy14 = 1 | |
| I0407 16:20:16.413460 1004 solver.cpp:406] Test net output #14: loss/accuracy15 = 1 | |
| I0407 16:20:16.413470 1004 solver.cpp:406] Test net output #15: loss/accuracy16 = 1 | |
| I0407 16:20:16.413480 1004 solver.cpp:406] Test net output #16: loss/accuracy17 = 1 | |
| I0407 16:20:16.413491 1004 solver.cpp:406] Test net output #17: loss/accuracy18 = 1 | |
| I0407 16:20:16.413502 1004 solver.cpp:406] Test net output #18: loss/accuracy19 = 1 | |
| I0407 16:20:16.413514 1004 solver.cpp:406] Test net output #19: loss/accuracy20 = 1 | |
| I0407 16:20:16.413525 1004 solver.cpp:406] Test net output #20: loss/accuracy21 = 1 | |
| I0407 16:20:16.413537 1004 solver.cpp:406] Test net output #21: loss/accuracy22 = 1 | |
| I0407 16:20:16.413552 1004 solver.cpp:406] Test net output #22: loss/loss01 = 3.38206 (* 0.0454545 = 0.15373 loss) | |
| I0407 16:20:16.413565 1004 solver.cpp:406] Test net output #23: loss/loss02 = 3.54658 (* 0.0454545 = 0.161208 loss) | |
| I0407 16:20:16.413579 1004 solver.cpp:406] Test net output #24: loss/loss03 = 3.63565 (* 0.0454545 = 0.165257 loss) | |
| I0407 16:20:16.413592 1004 solver.cpp:406] Test net output #25: loss/loss04 = 3.57373 (* 0.0454545 = 0.162442 loss) | |
| I0407 16:20:16.413605 1004 solver.cpp:406] Test net output #26: loss/loss05 = 3.37663 (* 0.0454545 = 0.153483 loss) | |
| I0407 16:20:16.413619 1004 solver.cpp:406] Test net output #27: loss/loss06 = 2.46154 (* 0.0454545 = 0.111888 loss) | |
| I0407 16:20:16.413632 1004 solver.cpp:406] Test net output #28: loss/loss07 = 0.814221 (* 0.0454545 = 0.0370101 loss) | |
| I0407 16:20:16.413645 1004 solver.cpp:406] Test net output #29: loss/loss08 = 0.295089 (* 0.0454545 = 0.0134132 loss) | |
| I0407 16:20:16.413660 1004 solver.cpp:406] Test net output #30: loss/loss09 = 0.0734698 (* 0.0454545 = 0.00333953 loss) | |
| I0407 16:20:16.413673 1004 solver.cpp:406] Test net output #31: loss/loss10 = 0.0403015 (* 0.0454545 = 0.00183188 loss) | |
| I0407 16:20:16.413687 1004 solver.cpp:406] Test net output #32: loss/loss11 = 0.00410927 (* 0.0454545 = 0.000186785 loss) | |
| I0407 16:20:16.413702 1004 solver.cpp:406] Test net output #33: loss/loss12 = 0.00420946 (* 0.0454545 = 0.000191339 loss) | |
| I0407 16:20:16.413715 1004 solver.cpp:406] Test net output #34: loss/loss13 = 0.00411855 (* 0.0454545 = 0.000187207 loss) | |
| I0407 16:20:16.413729 1004 solver.cpp:406] Test net output #35: loss/loss14 = 0.00405215 (* 0.0454545 = 0.000184189 loss) | |
| I0407 16:20:16.413743 1004 solver.cpp:406] Test net output #36: loss/loss15 = 0.00403179 (* 0.0454545 = 0.000183263 loss) | |
| I0407 16:20:16.413756 1004 solver.cpp:406] Test net output #37: loss/loss16 = 0.00412859 (* 0.0454545 = 0.000187663 loss) | |
| I0407 16:20:16.413770 1004 solver.cpp:406] Test net output #38: loss/loss17 = 0.00408151 (* 0.0454545 = 0.000185523 loss) | |
| I0407 16:20:16.413820 1004 solver.cpp:406] Test net output #39: loss/loss18 = 0.0041037 (* 0.0454545 = 0.000186532 loss) | |
| I0407 16:20:16.413835 1004 solver.cpp:406] Test net output #40: loss/loss19 = 0.00410148 (* 0.0454545 = 0.000186431 loss) | |
| I0407 16:20:16.413848 1004 solver.cpp:406] Test net output #41: loss/loss20 = 0.00411507 (* 0.0454545 = 0.000187049 loss) | |
| I0407 16:20:16.413862 1004 solver.cpp:406] Test net output #42: loss/loss21 = 0.00392023 (* 0.0454545 = 0.000178192 loss) | |
| I0407 16:20:16.413877 1004 solver.cpp:406] Test net output #43: loss/loss22 = 0.00407307 (* 0.0454545 = 0.000185139 loss) | |
| I0407 16:20:16.413887 1004 solver.cpp:406] Test net output #44: total_accuracy = 0.001 | |
| I0407 16:20:16.413899 1004 solver.cpp:406] Test net output #45: total_confidence = 0.000110406 | |
| I0407 16:20:16.436472 1004 solver.cpp:229] Iteration 50000, loss = 1.02003 | |
| I0407 16:20:16.436508 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:20:16.436525 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:20:16.436537 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:20:16.436549 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 16:20:16.436563 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 16:20:16.436575 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 16:20:16.436588 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.625 | |
| I0407 16:20:16.436599 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 16:20:16.436610 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:20:16.436622 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:20:16.436633 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:20:16.436645 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:20:16.436657 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:20:16.436668 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:20:16.436679 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:20:16.436691 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:20:16.436702 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:20:16.436714 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:20:16.436725 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:20:16.436738 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:20:16.436748 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:20:16.436760 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:20:16.436774 1004 solver.cpp:245] Train net output #22: loss/loss01 = 2.9178 (* 0.0454545 = 0.132627 loss) | |
| I0407 16:20:16.436789 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.64962 (* 0.0454545 = 0.165892 loss) | |
| I0407 16:20:16.436802 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.65102 (* 0.0454545 = 0.165955 loss) | |
| I0407 16:20:16.436815 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.35049 (* 0.0454545 = 0.152295 loss) | |
| I0407 16:20:16.436830 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.26269 (* 0.0454545 = 0.148304 loss) | |
| I0407 16:20:16.436842 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.82166 (* 0.0454545 = 0.128257 loss) | |
| I0407 16:20:16.436856 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.81725 (* 0.0454545 = 0.0826022 loss) | |
| I0407 16:20:16.436871 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.12709 (* 0.0454545 = 0.0512315 loss) | |
| I0407 16:20:16.436883 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0335903 (* 0.0454545 = 0.00152683 loss) | |
| I0407 16:20:16.436898 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.011822 (* 0.0454545 = 0.000537365 loss) | |
| I0407 16:20:16.436929 1004 solver.cpp:245] Train net output #32: loss/loss11 = 6.68393e-05 (* 0.0454545 = 3.03815e-06 loss) | |
| I0407 16:20:16.436945 1004 solver.cpp:245] Train net output #33: loss/loss12 = 7.4364e-05 (* 0.0454545 = 3.38018e-06 loss) | |
| I0407 16:20:16.436959 1004 solver.cpp:245] Train net output #34: loss/loss13 = 7.59375e-05 (* 0.0454545 = 3.45171e-06 loss) | |
| I0407 16:20:16.436974 1004 solver.cpp:245] Train net output #35: loss/loss14 = 7.4986e-05 (* 0.0454545 = 3.40845e-06 loss) | |
| I0407 16:20:16.436987 1004 solver.cpp:245] Train net output #36: loss/loss15 = 6.3841e-05 (* 0.0454545 = 2.90186e-06 loss) | |
| I0407 16:20:16.437002 1004 solver.cpp:245] Train net output #37: loss/loss16 = 6.68616e-05 (* 0.0454545 = 3.03916e-06 loss) | |
| I0407 16:20:16.437016 1004 solver.cpp:245] Train net output #38: loss/loss17 = 6.71528e-05 (* 0.0454545 = 3.0524e-06 loss) | |
| I0407 16:20:16.437031 1004 solver.cpp:245] Train net output #39: loss/loss18 = 7.2598e-05 (* 0.0454545 = 3.29991e-06 loss) | |
| I0407 16:20:16.437043 1004 solver.cpp:245] Train net output #40: loss/loss19 = 6.11213e-05 (* 0.0454545 = 2.77824e-06 loss) | |
| I0407 16:20:16.437057 1004 solver.cpp:245] Train net output #41: loss/loss20 = 6.4018e-05 (* 0.0454545 = 2.90991e-06 loss) | |
| I0407 16:20:16.437072 1004 solver.cpp:245] Train net output #42: loss/loss21 = 6.30739e-05 (* 0.0454545 = 2.86699e-06 loss) | |
| I0407 16:20:16.437089 1004 solver.cpp:245] Train net output #43: loss/loss22 = 6.27822e-05 (* 0.0454545 = 2.85373e-06 loss) | |
| I0407 16:20:16.437101 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:20:16.437113 1004 solver.cpp:245] Train net output #45: total_confidence = 7.22712e-06 | |
| I0407 16:20:16.437127 1004 sgd_solver.cpp:106] Iteration 50000, lr = 0.0009 | |
| I0407 16:20:55.636472 1004 solver.cpp:229] Iteration 50500, loss = 1.0168 | |
| I0407 16:20:55.636641 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:20:55.636663 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.125 | |
| I0407 16:20:55.636677 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:20:55.636689 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 16:20:55.636701 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.0625 | |
| I0407 16:20:55.636713 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.25 | |
| I0407 16:20:55.636725 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 16:20:55.636739 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:20:55.636750 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:20:55.636762 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:20:55.636775 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:20:55.636785 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:20:55.636797 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:20:55.636808 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:20:55.636821 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:20:55.636832 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:20:55.636844 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:20:55.636855 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:20:55.636867 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:20:55.636878 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:20:55.636889 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:20:55.636901 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:20:55.636916 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.12137 (* 0.0454545 = 0.14188 loss) | |
| I0407 16:20:55.636934 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.4702 (* 0.0454545 = 0.157736 loss) | |
| I0407 16:20:55.636947 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.57942 (* 0.0454545 = 0.162701 loss) | |
| I0407 16:20:55.636961 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.47479 (* 0.0454545 = 0.157945 loss) | |
| I0407 16:20:55.636976 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.60272 (* 0.0454545 = 0.16376 loss) | |
| I0407 16:20:55.636989 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.16868 (* 0.0454545 = 0.144031 loss) | |
| I0407 16:20:55.637003 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.915646 (* 0.0454545 = 0.0416203 loss) | |
| I0407 16:20:55.637017 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.387559 (* 0.0454545 = 0.0176163 loss) | |
| I0407 16:20:55.637032 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0431213 (* 0.0454545 = 0.00196006 loss) | |
| I0407 16:20:55.637045 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0170652 (* 0.0454545 = 0.00077569 loss) | |
| I0407 16:20:55.637060 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000106813 (* 0.0454545 = 4.85512e-06 loss) | |
| I0407 16:20:55.637074 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000106916 (* 0.0454545 = 4.8598e-06 loss) | |
| I0407 16:20:55.637089 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000104619 (* 0.0454545 = 4.75542e-06 loss) | |
| I0407 16:20:55.637102 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000105724 (* 0.0454545 = 4.80565e-06 loss) | |
| I0407 16:20:55.637116 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000105333 (* 0.0454545 = 4.78784e-06 loss) | |
| I0407 16:20:55.637130 1004 solver.cpp:245] Train net output #37: loss/loss16 = 9.9431e-05 (* 0.0454545 = 4.51959e-06 loss) | |
| I0407 16:20:55.637145 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000102692 (* 0.0454545 = 4.6678e-06 loss) | |
| I0407 16:20:55.637173 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000115726 (* 0.0454545 = 5.26029e-06 loss) | |
| I0407 16:20:55.637188 1004 solver.cpp:245] Train net output #40: loss/loss19 = 9.30766e-05 (* 0.0454545 = 4.23076e-06 loss) | |
| I0407 16:20:55.637202 1004 solver.cpp:245] Train net output #41: loss/loss20 = 9.83394e-05 (* 0.0454545 = 4.46997e-06 loss) | |
| I0407 16:20:55.637217 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000104665 (* 0.0454545 = 4.75751e-06 loss) | |
| I0407 16:20:55.637230 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000108709 (* 0.0454545 = 4.9413e-06 loss) | |
| I0407 16:20:55.637243 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:20:55.637254 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000350033 | |
| I0407 16:20:55.637267 1004 sgd_solver.cpp:106] Iteration 50500, lr = 0.000899 | |
| I0407 16:21:34.218384 1004 solver.cpp:229] Iteration 51000, loss = 1.02838 | |
| I0407 16:21:34.218489 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:21:34.218509 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:21:34.218523 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:21:34.218535 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 16:21:34.218547 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 16:21:34.218559 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.25 | |
| I0407 16:21:34.218571 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 16:21:34.218582 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:21:34.218595 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:21:34.218607 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:21:34.218618 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:21:34.218631 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:21:34.218642 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:21:34.218653 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:21:34.218665 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:21:34.218677 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:21:34.218688 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:21:34.218700 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:21:34.218711 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:21:34.218724 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:21:34.218735 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:21:34.218746 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:21:34.218762 1004 solver.cpp:245] Train net output #22: loss/loss01 = 4.01777 (* 0.0454545 = 0.182626 loss) | |
| I0407 16:21:34.218776 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.97722 (* 0.0454545 = 0.180783 loss) | |
| I0407 16:21:34.218791 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.6578 (* 0.0454545 = 0.166264 loss) | |
| I0407 16:21:34.218804 1004 solver.cpp:245] Train net output #25: loss/loss04 = 4.04686 (* 0.0454545 = 0.183948 loss) | |
| I0407 16:21:34.218818 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.87643 (* 0.0454545 = 0.176202 loss) | |
| I0407 16:21:34.218832 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.32837 (* 0.0454545 = 0.151289 loss) | |
| I0407 16:21:34.218845 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.36997 (* 0.0454545 = 0.0622715 loss) | |
| I0407 16:21:34.218859 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.439549 (* 0.0454545 = 0.0199795 loss) | |
| I0407 16:21:34.218873 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0578558 (* 0.0454545 = 0.00262981 loss) | |
| I0407 16:21:34.218888 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0368158 (* 0.0454545 = 0.00167345 loss) | |
| I0407 16:21:34.218901 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000565793 (* 0.0454545 = 2.57179e-05 loss) | |
| I0407 16:21:34.218915 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00053786 (* 0.0454545 = 2.44482e-05 loss) | |
| I0407 16:21:34.218933 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000528956 (* 0.0454545 = 2.40435e-05 loss) | |
| I0407 16:21:34.218947 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000552506 (* 0.0454545 = 2.51139e-05 loss) | |
| I0407 16:21:34.218961 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000574413 (* 0.0454545 = 2.61097e-05 loss) | |
| I0407 16:21:34.218976 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000525945 (* 0.0454545 = 2.39066e-05 loss) | |
| I0407 16:21:34.218991 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000559109 (* 0.0454545 = 2.5414e-05 loss) | |
| I0407 16:21:34.219022 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000580217 (* 0.0454545 = 2.63735e-05 loss) | |
| I0407 16:21:34.219036 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000481728 (* 0.0454545 = 2.18967e-05 loss) | |
| I0407 16:21:34.219050 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000522084 (* 0.0454545 = 2.37311e-05 loss) | |
| I0407 16:21:34.219064 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000566136 (* 0.0454545 = 2.57334e-05 loss) | |
| I0407 16:21:34.219079 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000542092 (* 0.0454545 = 2.46406e-05 loss) | |
| I0407 16:21:34.219089 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:21:34.219101 1004 solver.cpp:245] Train net output #45: total_confidence = 1.85854e-05 | |
| I0407 16:21:34.219115 1004 sgd_solver.cpp:106] Iteration 51000, lr = 0.000898 | |
| I0407 16:22:13.060214 1004 solver.cpp:229] Iteration 51500, loss = 1.01754 | |
| I0407 16:22:13.060293 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:22:13.060312 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:22:13.060324 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:22:13.060336 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 16:22:13.060348 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.5 | |
| I0407 16:22:13.060360 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.625 | |
| I0407 16:22:13.060374 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 16:22:13.060385 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 16:22:13.060397 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:22:13.060410 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:22:13.060420 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:22:13.060432 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:22:13.060444 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:22:13.060456 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:22:13.060467 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:22:13.060478 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:22:13.060494 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:22:13.060505 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:22:13.060518 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:22:13.060528 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:22:13.060540 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:22:13.060551 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:22:13.060567 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.07978 (* 0.0454545 = 0.13999 loss) | |
| I0407 16:22:13.060582 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.34038 (* 0.0454545 = 0.151835 loss) | |
| I0407 16:22:13.060596 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.39869 (* 0.0454545 = 0.154486 loss) | |
| I0407 16:22:13.060611 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.37148 (* 0.0454545 = 0.153249 loss) | |
| I0407 16:22:13.060624 1004 solver.cpp:245] Train net output #26: loss/loss05 = 2.3752 (* 0.0454545 = 0.107964 loss) | |
| I0407 16:22:13.060637 1004 solver.cpp:245] Train net output #27: loss/loss06 = 1.68347 (* 0.0454545 = 0.0765212 loss) | |
| I0407 16:22:13.060652 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.947697 (* 0.0454545 = 0.0430771 loss) | |
| I0407 16:22:13.060667 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.0843181 (* 0.0454545 = 0.00383264 loss) | |
| I0407 16:22:13.060680 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0220024 (* 0.0454545 = 0.00100011 loss) | |
| I0407 16:22:13.060694 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.00887618 (* 0.0454545 = 0.000403463 loss) | |
| I0407 16:22:13.060709 1004 solver.cpp:245] Train net output #32: loss/loss11 = 2.06913e-05 (* 0.0454545 = 9.40512e-07 loss) | |
| I0407 16:22:13.060724 1004 solver.cpp:245] Train net output #33: loss/loss12 = 2.0885e-05 (* 0.0454545 = 9.4932e-07 loss) | |
| I0407 16:22:13.060737 1004 solver.cpp:245] Train net output #34: loss/loss13 = 1.89403e-05 (* 0.0454545 = 8.60922e-07 loss) | |
| I0407 16:22:13.060751 1004 solver.cpp:245] Train net output #35: loss/loss14 = 2.1332e-05 (* 0.0454545 = 9.69637e-07 loss) | |
| I0407 16:22:13.060766 1004 solver.cpp:245] Train net output #36: loss/loss15 = 2.06688e-05 (* 0.0454545 = 9.39493e-07 loss) | |
| I0407 16:22:13.060781 1004 solver.cpp:245] Train net output #37: loss/loss16 = 2.13769e-05 (* 0.0454545 = 9.71675e-07 loss) | |
| I0407 16:22:13.060794 1004 solver.cpp:245] Train net output #38: loss/loss17 = 1.94543e-05 (* 0.0454545 = 8.84287e-07 loss) | |
| I0407 16:22:13.060824 1004 solver.cpp:245] Train net output #39: loss/loss18 = 2.33588e-05 (* 0.0454545 = 1.06176e-06 loss) | |
| I0407 16:22:13.060839 1004 solver.cpp:245] Train net output #40: loss/loss19 = 1.9134e-05 (* 0.0454545 = 8.69726e-07 loss) | |
| I0407 16:22:13.060853 1004 solver.cpp:245] Train net output #41: loss/loss20 = 1.93649e-05 (* 0.0454545 = 8.80224e-07 loss) | |
| I0407 16:22:13.060868 1004 solver.cpp:245] Train net output #42: loss/loss21 = 1.93127e-05 (* 0.0454545 = 8.77851e-07 loss) | |
| I0407 16:22:13.060883 1004 solver.cpp:245] Train net output #43: loss/loss22 = 2.29936e-05 (* 0.0454545 = 1.04517e-06 loss) | |
| I0407 16:22:13.060894 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:22:13.060905 1004 solver.cpp:245] Train net output #45: total_confidence = 9.15131e-05 | |
| I0407 16:22:13.060920 1004 sgd_solver.cpp:106] Iteration 51500, lr = 0.000897 | |
| I0407 16:22:52.001175 1004 solver.cpp:229] Iteration 52000, loss = 1.01487 | |
| I0407 16:22:52.001287 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:22:52.001307 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:22:52.001319 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 16:22:52.001332 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 16:22:52.001344 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.0625 | |
| I0407 16:22:52.001356 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.125 | |
| I0407 16:22:52.001368 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.5 | |
| I0407 16:22:52.001379 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.75 | |
| I0407 16:22:52.001391 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.875 | |
| I0407 16:22:52.001404 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:22:52.001415 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:22:52.001426 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:22:52.001438 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:22:52.001449 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:22:52.001461 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:22:52.001472 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:22:52.001484 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:22:52.001497 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:22:52.001507 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:22:52.001519 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:22:52.001530 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:22:52.001543 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:22:52.001557 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.51584 (* 0.0454545 = 0.159811 loss) | |
| I0407 16:22:52.001572 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.59646 (* 0.0454545 = 0.163475 loss) | |
| I0407 16:22:52.001586 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.47805 (* 0.0454545 = 0.158093 loss) | |
| I0407 16:22:52.001600 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.89336 (* 0.0454545 = 0.176971 loss) | |
| I0407 16:22:52.001615 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.58873 (* 0.0454545 = 0.163124 loss) | |
| I0407 16:22:52.001628 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.52831 (* 0.0454545 = 0.160378 loss) | |
| I0407 16:22:52.001642 1004 solver.cpp:245] Train net output #28: loss/loss07 = 2.66441 (* 0.0454545 = 0.12111 loss) | |
| I0407 16:22:52.001657 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.51576 (* 0.0454545 = 0.0688981 loss) | |
| I0407 16:22:52.001670 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.906381 (* 0.0454545 = 0.0411992 loss) | |
| I0407 16:22:52.001684 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0213384 (* 0.0454545 = 0.000969928 loss) | |
| I0407 16:22:52.001698 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000186601 (* 0.0454545 = 8.48185e-06 loss) | |
| I0407 16:22:52.001713 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000176207 (* 0.0454545 = 8.00941e-06 loss) | |
| I0407 16:22:52.001727 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000165207 (* 0.0454545 = 7.50941e-06 loss) | |
| I0407 16:22:52.001741 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00017056 (* 0.0454545 = 7.75273e-06 loss) | |
| I0407 16:22:52.001755 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.00019716 (* 0.0454545 = 8.96181e-06 loss) | |
| I0407 16:22:52.001770 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000180743 (* 0.0454545 = 8.21557e-06 loss) | |
| I0407 16:22:52.001785 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000192118 (* 0.0454545 = 8.73264e-06 loss) | |
| I0407 16:22:52.001814 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000205353 (* 0.0454545 = 9.33422e-06 loss) | |
| I0407 16:22:52.001829 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000165469 (* 0.0454545 = 7.52133e-06 loss) | |
| I0407 16:22:52.001843 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.00017467 (* 0.0454545 = 7.93954e-06 loss) | |
| I0407 16:22:52.001857 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000204781 (* 0.0454545 = 9.30824e-06 loss) | |
| I0407 16:22:52.001871 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000199777 (* 0.0454545 = 9.08076e-06 loss) | |
| I0407 16:22:52.001883 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:22:52.001895 1004 solver.cpp:245] Train net output #45: total_confidence = 2.52798e-06 | |
| I0407 16:22:52.001909 1004 sgd_solver.cpp:106] Iteration 52000, lr = 0.000896 | |
| I0407 16:23:30.649839 1004 solver.cpp:229] Iteration 52500, loss = 1.01625 | |
| I0407 16:23:30.650017 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:23:30.650037 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:23:30.650050 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:23:30.650063 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 16:23:30.650074 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 16:23:30.650086 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 16:23:30.650099 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 16:23:30.650110 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 16:23:30.650121 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:23:30.650133 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:23:30.650144 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:23:30.650156 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:23:30.650168 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:23:30.650179 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:23:30.650190 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:23:30.650202 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:23:30.650213 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:23:30.650225 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:23:30.650236 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:23:30.650249 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:23:30.650260 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:23:30.650271 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:23:30.650287 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.5951 (* 0.0454545 = 0.163414 loss) | |
| I0407 16:23:30.650301 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.97566 (* 0.0454545 = 0.180712 loss) | |
| I0407 16:23:30.650315 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.71678 (* 0.0454545 = 0.168944 loss) | |
| I0407 16:23:30.650329 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.65096 (* 0.0454545 = 0.165953 loss) | |
| I0407 16:23:30.650342 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.33117 (* 0.0454545 = 0.151417 loss) | |
| I0407 16:23:30.650357 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.8259 (* 0.0454545 = 0.12845 loss) | |
| I0407 16:23:30.650370 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.50187 (* 0.0454545 = 0.0682667 loss) | |
| I0407 16:23:30.650384 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.741786 (* 0.0454545 = 0.0337175 loss) | |
| I0407 16:23:30.650398 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0402707 (* 0.0454545 = 0.00183049 loss) | |
| I0407 16:23:30.650413 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0173937 (* 0.0454545 = 0.000790621 loss) | |
| I0407 16:23:30.650427 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000234864 (* 0.0454545 = 1.06756e-05 loss) | |
| I0407 16:23:30.650441 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000187345 (* 0.0454545 = 8.51566e-06 loss) | |
| I0407 16:23:30.650455 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000217595 (* 0.0454545 = 9.89067e-06 loss) | |
| I0407 16:23:30.650470 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000225674 (* 0.0454545 = 1.02579e-05 loss) | |
| I0407 16:23:30.650483 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000245241 (* 0.0454545 = 1.11473e-05 loss) | |
| I0407 16:23:30.650497 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.00020354 (* 0.0454545 = 9.2518e-06 loss) | |
| I0407 16:23:30.650512 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000215562 (* 0.0454545 = 9.79827e-06 loss) | |
| I0407 16:23:30.650820 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000256326 (* 0.0454545 = 1.16512e-05 loss) | |
| I0407 16:23:30.650836 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000198576 (* 0.0454545 = 9.02619e-06 loss) | |
| I0407 16:23:30.650849 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000201878 (* 0.0454545 = 9.17628e-06 loss) | |
| I0407 16:23:30.650863 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000242344 (* 0.0454545 = 1.10156e-05 loss) | |
| I0407 16:23:30.650877 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000215493 (* 0.0454545 = 9.79513e-06 loss) | |
| I0407 16:23:30.650889 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:23:30.650900 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000198366 | |
| I0407 16:23:30.650913 1004 sgd_solver.cpp:106] Iteration 52500, lr = 0.000895 | |
| I0407 16:24:09.318362 1004 solver.cpp:229] Iteration 53000, loss = 1.01729 | |
| I0407 16:24:09.318435 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:24:09.318454 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:24:09.318467 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:24:09.318480 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 16:24:09.318492 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.0625 | |
| I0407 16:24:09.318505 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.1875 | |
| I0407 16:24:09.318516 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.375 | |
| I0407 16:24:09.318528 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.6875 | |
| I0407 16:24:09.318541 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.875 | |
| I0407 16:24:09.318552 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 16:24:09.318563 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:24:09.318575 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:24:09.318586 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:24:09.318598 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:24:09.318610 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:24:09.318621 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:24:09.318637 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:24:09.318650 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:24:09.318661 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:24:09.318673 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:24:09.318684 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:24:09.318696 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:24:09.318711 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.24234 (* 0.0454545 = 0.147379 loss) | |
| I0407 16:24:09.318727 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.60207 (* 0.0454545 = 0.163731 loss) | |
| I0407 16:24:09.318740 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.61204 (* 0.0454545 = 0.164183 loss) | |
| I0407 16:24:09.318754 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.55315 (* 0.0454545 = 0.161507 loss) | |
| I0407 16:24:09.318768 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.35547 (* 0.0454545 = 0.152522 loss) | |
| I0407 16:24:09.318783 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.31402 (* 0.0454545 = 0.150637 loss) | |
| I0407 16:24:09.318796 1004 solver.cpp:245] Train net output #28: loss/loss07 = 2.54919 (* 0.0454545 = 0.115872 loss) | |
| I0407 16:24:09.318810 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.39877 (* 0.0454545 = 0.0635805 loss) | |
| I0407 16:24:09.318825 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.655253 (* 0.0454545 = 0.0297842 loss) | |
| I0407 16:24:09.318838 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.388883 (* 0.0454545 = 0.0176765 loss) | |
| I0407 16:24:09.318852 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000720164 (* 0.0454545 = 3.27347e-05 loss) | |
| I0407 16:24:09.318866 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000714265 (* 0.0454545 = 3.24666e-05 loss) | |
| I0407 16:24:09.318881 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000720162 (* 0.0454545 = 3.27346e-05 loss) | |
| I0407 16:24:09.318895 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000739257 (* 0.0454545 = 3.36026e-05 loss) | |
| I0407 16:24:09.318909 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.0007444 (* 0.0454545 = 3.38363e-05 loss) | |
| I0407 16:24:09.318923 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000711671 (* 0.0454545 = 3.23487e-05 loss) | |
| I0407 16:24:09.318938 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000731012 (* 0.0454545 = 3.32278e-05 loss) | |
| I0407 16:24:09.318969 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000780474 (* 0.0454545 = 3.54761e-05 loss) | |
| I0407 16:24:09.318984 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000710393 (* 0.0454545 = 3.22906e-05 loss) | |
| I0407 16:24:09.318999 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000745 (* 0.0454545 = 3.38636e-05 loss) | |
| I0407 16:24:09.319013 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000752752 (* 0.0454545 = 3.4216e-05 loss) | |
| I0407 16:24:09.319027 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000821652 (* 0.0454545 = 3.73478e-05 loss) | |
| I0407 16:24:09.319039 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:24:09.319051 1004 solver.cpp:245] Train net output #45: total_confidence = 8.67963e-05 | |
| I0407 16:24:09.319063 1004 sgd_solver.cpp:106] Iteration 53000, lr = 0.000894 | |
| I0407 16:24:47.866300 1004 solver.cpp:229] Iteration 53500, loss = 1.01938 | |
| I0407 16:24:47.866484 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:24:47.866503 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:24:47.866516 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:24:47.866528 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 16:24:47.866540 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.0625 | |
| I0407 16:24:47.866552 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.25 | |
| I0407 16:24:47.866564 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.625 | |
| I0407 16:24:47.866576 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:24:47.866588 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:24:47.866600 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:24:47.866611 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:24:47.866623 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:24:47.866636 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:24:47.866647 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:24:47.866658 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:24:47.866669 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:24:47.866682 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:24:47.866693 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:24:47.866704 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:24:47.866716 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:24:47.866727 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:24:47.866739 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:24:47.866755 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.41426 (* 0.0454545 = 0.155193 loss) | |
| I0407 16:24:47.866770 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.66316 (* 0.0454545 = 0.166507 loss) | |
| I0407 16:24:47.866783 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.92811 (* 0.0454545 = 0.17855 loss) | |
| I0407 16:24:47.866796 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.57154 (* 0.0454545 = 0.162343 loss) | |
| I0407 16:24:47.866811 1004 solver.cpp:245] Train net output #26: loss/loss05 = 4.11929 (* 0.0454545 = 0.18724 loss) | |
| I0407 16:24:47.866824 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.21366 (* 0.0454545 = 0.146075 loss) | |
| I0407 16:24:47.866838 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.70142 (* 0.0454545 = 0.0773372 loss) | |
| I0407 16:24:47.866852 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.371683 (* 0.0454545 = 0.0168947 loss) | |
| I0407 16:24:47.866866 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0295644 (* 0.0454545 = 0.00134384 loss) | |
| I0407 16:24:47.866880 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.012629 (* 0.0454545 = 0.000574044 loss) | |
| I0407 16:24:47.866894 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000100902 (* 0.0454545 = 4.58646e-06 loss) | |
| I0407 16:24:47.866909 1004 solver.cpp:245] Train net output #33: loss/loss12 = 9.25896e-05 (* 0.0454545 = 4.20862e-06 loss) | |
| I0407 16:24:47.866922 1004 solver.cpp:245] Train net output #34: loss/loss13 = 9.39035e-05 (* 0.0454545 = 4.26834e-06 loss) | |
| I0407 16:24:47.866936 1004 solver.cpp:245] Train net output #35: loss/loss14 = 9.98418e-05 (* 0.0454545 = 4.53826e-06 loss) | |
| I0407 16:24:47.866950 1004 solver.cpp:245] Train net output #36: loss/loss15 = 9.94347e-05 (* 0.0454545 = 4.51976e-06 loss) | |
| I0407 16:24:47.866964 1004 solver.cpp:245] Train net output #37: loss/loss16 = 9.90539e-05 (* 0.0454545 = 4.50245e-06 loss) | |
| I0407 16:24:47.866978 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000104561 (* 0.0454545 = 4.75276e-06 loss) | |
| I0407 16:24:47.867009 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000125618 (* 0.0454545 = 5.7099e-06 loss) | |
| I0407 16:24:47.867024 1004 solver.cpp:245] Train net output #40: loss/loss19 = 9.93453e-05 (* 0.0454545 = 4.51569e-06 loss) | |
| I0407 16:24:47.867038 1004 solver.cpp:245] Train net output #41: loss/loss20 = 9.41023e-05 (* 0.0454545 = 4.27738e-06 loss) | |
| I0407 16:24:47.867053 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00011597 (* 0.0454545 = 5.27137e-06 loss) | |
| I0407 16:24:47.867066 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000105105 (* 0.0454545 = 4.77748e-06 loss) | |
| I0407 16:24:47.867081 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:24:47.867094 1004 solver.cpp:245] Train net output #45: total_confidence = 6.32692e-05 | |
| I0407 16:24:47.867106 1004 sgd_solver.cpp:106] Iteration 53500, lr = 0.000893 | |
| I0407 16:25:26.519111 1004 solver.cpp:229] Iteration 54000, loss = 1.01137 | |
| I0407 16:25:26.519232 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:25:26.519253 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:25:26.519266 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:25:26.519279 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 16:25:26.519290 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.3125 | |
| I0407 16:25:26.519304 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 16:25:26.519315 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 16:25:26.519327 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 16:25:26.519340 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:25:26.519351 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:25:26.519376 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:25:26.519388 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:25:26.519402 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:25:26.519412 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:25:26.519425 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:25:26.519436 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:25:26.519448 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:25:26.519460 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:25:26.519471 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:25:26.519484 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:25:26.519495 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:25:26.519506 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:25:26.519522 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.6492 (* 0.0454545 = 0.165873 loss) | |
| I0407 16:25:26.519537 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.68946 (* 0.0454545 = 0.167703 loss) | |
| I0407 16:25:26.519551 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.854 (* 0.0454545 = 0.175182 loss) | |
| I0407 16:25:26.519565 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.65611 (* 0.0454545 = 0.166187 loss) | |
| I0407 16:25:26.519579 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.06221 (* 0.0454545 = 0.139191 loss) | |
| I0407 16:25:26.519593 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.96258 (* 0.0454545 = 0.134663 loss) | |
| I0407 16:25:26.519608 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.4402 (* 0.0454545 = 0.0654636 loss) | |
| I0407 16:25:26.519621 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.0472331 (* 0.0454545 = 0.00214696 loss) | |
| I0407 16:25:26.519635 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0231605 (* 0.0454545 = 0.00105275 loss) | |
| I0407 16:25:26.519649 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.014418 (* 0.0454545 = 0.000655364 loss) | |
| I0407 16:25:26.519665 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000398069 (* 0.0454545 = 1.8094e-05 loss) | |
| I0407 16:25:26.519678 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000385715 (* 0.0454545 = 1.75325e-05 loss) | |
| I0407 16:25:26.519692 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000368781 (* 0.0454545 = 1.67628e-05 loss) | |
| I0407 16:25:26.519707 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00040776 (* 0.0454545 = 1.85346e-05 loss) | |
| I0407 16:25:26.519721 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000439924 (* 0.0454545 = 1.99965e-05 loss) | |
| I0407 16:25:26.519736 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000405084 (* 0.0454545 = 1.84129e-05 loss) | |
| I0407 16:25:26.519749 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000418718 (* 0.0454545 = 1.90326e-05 loss) | |
| I0407 16:25:26.519781 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000505376 (* 0.0454545 = 2.29717e-05 loss) | |
| I0407 16:25:26.519796 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000401743 (* 0.0454545 = 1.8261e-05 loss) | |
| I0407 16:25:26.519811 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000377367 (* 0.0454545 = 1.7153e-05 loss) | |
| I0407 16:25:26.519825 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000450604 (* 0.0454545 = 2.0482e-05 loss) | |
| I0407 16:25:26.519840 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000455927 (* 0.0454545 = 2.0724e-05 loss) | |
| I0407 16:25:26.519851 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:25:26.519863 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000283178 | |
| I0407 16:25:26.519876 1004 sgd_solver.cpp:106] Iteration 54000, lr = 0.000892 | |
| I0407 16:26:05.222785 1004 solver.cpp:229] Iteration 54500, loss = 1.01549 | |
| I0407 16:26:05.222939 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:26:05.222960 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:26:05.222975 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 16:26:05.222986 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 16:26:05.222998 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 16:26:05.223011 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 16:26:05.223022 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 16:26:05.223034 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 16:26:05.223047 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:26:05.223057 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:26:05.223069 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:26:05.223080 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:26:05.223093 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:26:05.223104 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:26:05.223116 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:26:05.223129 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:26:05.223140 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:26:05.223151 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:26:05.223162 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:26:05.223175 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:26:05.223186 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:26:05.223196 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:26:05.223212 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.13016 (* 0.0454545 = 0.14228 loss) | |
| I0407 16:26:05.223227 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.4675 (* 0.0454545 = 0.157613 loss) | |
| I0407 16:26:05.223242 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.49319 (* 0.0454545 = 0.158781 loss) | |
| I0407 16:26:05.223255 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.84463 (* 0.0454545 = 0.174756 loss) | |
| I0407 16:26:05.223268 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.33111 (* 0.0454545 = 0.151414 loss) | |
| I0407 16:26:05.223283 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.80887 (* 0.0454545 = 0.127676 loss) | |
| I0407 16:26:05.223296 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.42963 (* 0.0454545 = 0.0649832 loss) | |
| I0407 16:26:05.223310 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.0377516 (* 0.0454545 = 0.00171598 loss) | |
| I0407 16:26:05.223348 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0124445 (* 0.0454545 = 0.000565659 loss) | |
| I0407 16:26:05.223364 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.00556086 (* 0.0454545 = 0.000252766 loss) | |
| I0407 16:26:05.223379 1004 solver.cpp:245] Train net output #32: loss/loss11 = 8.17546e-05 (* 0.0454545 = 3.71612e-06 loss) | |
| I0407 16:26:05.223392 1004 solver.cpp:245] Train net output #33: loss/loss12 = 6.93182e-05 (* 0.0454545 = 3.15083e-06 loss) | |
| I0407 16:26:05.223407 1004 solver.cpp:245] Train net output #34: loss/loss13 = 6.90308e-05 (* 0.0454545 = 3.13776e-06 loss) | |
| I0407 16:26:05.223422 1004 solver.cpp:245] Train net output #35: loss/loss14 = 8.15763e-05 (* 0.0454545 = 3.70801e-06 loss) | |
| I0407 16:26:05.223435 1004 solver.cpp:245] Train net output #36: loss/loss15 = 8.41624e-05 (* 0.0454545 = 3.82556e-06 loss) | |
| I0407 16:26:05.223449 1004 solver.cpp:245] Train net output #37: loss/loss16 = 7.60005e-05 (* 0.0454545 = 3.45457e-06 loss) | |
| I0407 16:26:05.223464 1004 solver.cpp:245] Train net output #38: loss/loss17 = 7.97535e-05 (* 0.0454545 = 3.62516e-06 loss) | |
| I0407 16:26:05.223491 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000100225 (* 0.0454545 = 4.55568e-06 loss) | |
| I0407 16:26:05.223507 1004 solver.cpp:245] Train net output #40: loss/loss19 = 6.99028e-05 (* 0.0454545 = 3.1774e-06 loss) | |
| I0407 16:26:05.223521 1004 solver.cpp:245] Train net output #41: loss/loss20 = 7.72645e-05 (* 0.0454545 = 3.51202e-06 loss) | |
| I0407 16:26:05.223536 1004 solver.cpp:245] Train net output #42: loss/loss21 = 9.23293e-05 (* 0.0454545 = 4.19679e-06 loss) | |
| I0407 16:26:05.223567 1004 solver.cpp:245] Train net output #43: loss/loss22 = 8.48109e-05 (* 0.0454545 = 3.85504e-06 loss) | |
| I0407 16:26:05.223582 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:26:05.223593 1004 solver.cpp:245] Train net output #45: total_confidence = 0.0004599 | |
| I0407 16:26:05.223606 1004 sgd_solver.cpp:106] Iteration 54500, lr = 0.000891 | |
| I0407 16:26:44.004312 1004 solver.cpp:338] Iteration 55000, Testing net (#0) | |
| I0407 16:26:51.989516 1004 solver.cpp:393] Test loss: 0.894567 | |
| I0407 16:26:51.989567 1004 solver.cpp:406] Test net output #0: loss/accuracy01 = 0.421 | |
| I0407 16:26:51.989583 1004 solver.cpp:406] Test net output #1: loss/accuracy02 = 0.075 | |
| I0407 16:26:51.989595 1004 solver.cpp:406] Test net output #2: loss/accuracy03 = 0.089 | |
| I0407 16:26:51.989608 1004 solver.cpp:406] Test net output #3: loss/accuracy04 = 0.08 | |
| I0407 16:26:51.989619 1004 solver.cpp:406] Test net output #4: loss/accuracy05 = 0.202 | |
| I0407 16:26:51.989631 1004 solver.cpp:406] Test net output #5: loss/accuracy06 = 0.497 | |
| I0407 16:26:51.989642 1004 solver.cpp:406] Test net output #6: loss/accuracy07 = 0.894 | |
| I0407 16:26:51.989655 1004 solver.cpp:406] Test net output #7: loss/accuracy08 = 0.97 | |
| I0407 16:26:51.989665 1004 solver.cpp:406] Test net output #8: loss/accuracy09 = 0.995 | |
| I0407 16:26:51.989676 1004 solver.cpp:406] Test net output #9: loss/accuracy10 = 0.998 | |
| I0407 16:26:51.989687 1004 solver.cpp:406] Test net output #10: loss/accuracy11 = 1 | |
| I0407 16:26:51.989698 1004 solver.cpp:406] Test net output #11: loss/accuracy12 = 1 | |
| I0407 16:26:51.989709 1004 solver.cpp:406] Test net output #12: loss/accuracy13 = 1 | |
| I0407 16:26:51.989722 1004 solver.cpp:406] Test net output #13: loss/accuracy14 = 1 | |
| I0407 16:26:51.989732 1004 solver.cpp:406] Test net output #14: loss/accuracy15 = 1 | |
| I0407 16:26:51.989743 1004 solver.cpp:406] Test net output #15: loss/accuracy16 = 1 | |
| I0407 16:26:51.989753 1004 solver.cpp:406] Test net output #16: loss/accuracy17 = 1 | |
| I0407 16:26:51.989765 1004 solver.cpp:406] Test net output #17: loss/accuracy18 = 1 | |
| I0407 16:26:51.989776 1004 solver.cpp:406] Test net output #18: loss/accuracy19 = 1 | |
| I0407 16:26:51.989787 1004 solver.cpp:406] Test net output #19: loss/accuracy20 = 1 | |
| I0407 16:26:51.989799 1004 solver.cpp:406] Test net output #20: loss/accuracy21 = 1 | |
| I0407 16:26:51.989809 1004 solver.cpp:406] Test net output #21: loss/accuracy22 = 1 | |
| I0407 16:26:51.989823 1004 solver.cpp:406] Test net output #22: loss/loss01 = 2.93143 (* 0.0454545 = 0.133247 loss) | |
| I0407 16:26:51.989840 1004 solver.cpp:406] Test net output #23: loss/loss02 = 3.30121 (* 0.0454545 = 0.150055 loss) | |
| I0407 16:26:51.989852 1004 solver.cpp:406] Test net output #24: loss/loss03 = 3.36547 (* 0.0454545 = 0.152976 loss) | |
| I0407 16:26:51.989866 1004 solver.cpp:406] Test net output #25: loss/loss04 = 3.35422 (* 0.0454545 = 0.152465 loss) | |
| I0407 16:26:51.989879 1004 solver.cpp:406] Test net output #26: loss/loss05 = 3.24041 (* 0.0454545 = 0.147291 loss) | |
| I0407 16:26:51.989893 1004 solver.cpp:406] Test net output #27: loss/loss06 = 2.31057 (* 0.0454545 = 0.105026 loss) | |
| I0407 16:26:51.989907 1004 solver.cpp:406] Test net output #28: loss/loss07 = 0.766983 (* 0.0454545 = 0.0348629 loss) | |
| I0407 16:26:51.989923 1004 solver.cpp:406] Test net output #29: loss/loss08 = 0.277015 (* 0.0454545 = 0.0125916 loss) | |
| I0407 16:26:51.989938 1004 solver.cpp:406] Test net output #30: loss/loss09 = 0.0663103 (* 0.0454545 = 0.0030141 loss) | |
| I0407 16:26:51.989953 1004 solver.cpp:406] Test net output #31: loss/loss10 = 0.038292 (* 0.0454545 = 0.00174055 loss) | |
| I0407 16:26:51.989965 1004 solver.cpp:406] Test net output #32: loss/loss11 = 0.00248213 (* 0.0454545 = 0.000112824 loss) | |
| I0407 16:26:51.989979 1004 solver.cpp:406] Test net output #33: loss/loss12 = 0.00245043 (* 0.0454545 = 0.000111383 loss) | |
| I0407 16:26:51.989994 1004 solver.cpp:406] Test net output #34: loss/loss13 = 0.00241126 (* 0.0454545 = 0.000109603 loss) | |
| I0407 16:26:51.990007 1004 solver.cpp:406] Test net output #35: loss/loss14 = 0.00235507 (* 0.0454545 = 0.000107049 loss) | |
| I0407 16:26:51.990021 1004 solver.cpp:406] Test net output #36: loss/loss15 = 0.00234189 (* 0.0454545 = 0.000106449 loss) | |
| I0407 16:26:51.990034 1004 solver.cpp:406] Test net output #37: loss/loss16 = 0.00239475 (* 0.0454545 = 0.000108852 loss) | |
| I0407 16:26:51.990048 1004 solver.cpp:406] Test net output #38: loss/loss17 = 0.00235637 (* 0.0454545 = 0.000107108 loss) | |
| I0407 16:26:51.990097 1004 solver.cpp:406] Test net output #39: loss/loss18 = 0.00245998 (* 0.0454545 = 0.000111817 loss) | |
| I0407 16:26:51.990113 1004 solver.cpp:406] Test net output #40: loss/loss19 = 0.00233713 (* 0.0454545 = 0.000106233 loss) | |
| I0407 16:26:51.990126 1004 solver.cpp:406] Test net output #41: loss/loss20 = 0.00233459 (* 0.0454545 = 0.000106118 loss) | |
| I0407 16:26:51.990140 1004 solver.cpp:406] Test net output #42: loss/loss21 = 0.0022839 (* 0.0454545 = 0.000103814 loss) | |
| I0407 16:26:51.990154 1004 solver.cpp:406] Test net output #43: loss/loss22 = 0.00237127 (* 0.0454545 = 0.000107785 loss) | |
| I0407 16:26:51.990165 1004 solver.cpp:406] Test net output #44: total_accuracy = 0 | |
| I0407 16:26:51.990177 1004 solver.cpp:406] Test net output #45: total_confidence = 0.000290701 | |
| I0407 16:26:52.012771 1004 solver.cpp:229] Iteration 55000, loss = 1.01007 | |
| I0407 16:26:52.012806 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:26:52.012823 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:26:52.012835 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 16:26:52.012847 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 16:26:52.012859 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.3125 | |
| I0407 16:26:52.012871 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 16:26:52.012883 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 16:26:52.012895 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:26:52.012907 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:26:52.012918 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 16:26:52.012929 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:26:52.012941 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:26:52.012956 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:26:52.012969 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:26:52.012979 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:26:52.012991 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:26:52.013002 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:26:52.013015 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:26:52.013025 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:26:52.013036 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:26:52.013047 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:26:52.013058 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:26:52.013075 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.51549 (* 0.0454545 = 0.159795 loss) | |
| I0407 16:26:52.013089 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.74826 (* 0.0454545 = 0.170376 loss) | |
| I0407 16:26:52.013103 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.73718 (* 0.0454545 = 0.169872 loss) | |
| I0407 16:26:52.013116 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.73649 (* 0.0454545 = 0.169841 loss) | |
| I0407 16:26:52.013130 1004 solver.cpp:245] Train net output #26: loss/loss05 = 2.92247 (* 0.0454545 = 0.13284 loss) | |
| I0407 16:26:52.013144 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.37047 (* 0.0454545 = 0.107749 loss) | |
| I0407 16:26:52.013157 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.12311 (* 0.0454545 = 0.0510507 loss) | |
| I0407 16:26:52.013171 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.313248 (* 0.0454545 = 0.0142385 loss) | |
| I0407 16:26:52.013185 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.293647 (* 0.0454545 = 0.0133476 loss) | |
| I0407 16:26:52.013198 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.404744 (* 0.0454545 = 0.0183974 loss) | |
| I0407 16:26:52.013229 1004 solver.cpp:245] Train net output #32: loss/loss11 = 3.85109e-05 (* 0.0454545 = 1.75049e-06 loss) | |
| I0407 16:26:52.013245 1004 solver.cpp:245] Train net output #33: loss/loss12 = 3.5605e-05 (* 0.0454545 = 1.61841e-06 loss) | |
| I0407 16:26:52.013259 1004 solver.cpp:245] Train net output #34: loss/loss13 = 3.66779e-05 (* 0.0454545 = 1.66718e-06 loss) | |
| I0407 16:26:52.013273 1004 solver.cpp:245] Train net output #35: loss/loss14 = 4.09179e-05 (* 0.0454545 = 1.8599e-06 loss) | |
| I0407 16:26:52.013288 1004 solver.cpp:245] Train net output #36: loss/loss15 = 4.47967e-05 (* 0.0454545 = 2.03621e-06 loss) | |
| I0407 16:26:52.013301 1004 solver.cpp:245] Train net output #37: loss/loss16 = 3.48262e-05 (* 0.0454545 = 1.58301e-06 loss) | |
| I0407 16:26:52.013315 1004 solver.cpp:245] Train net output #38: loss/loss17 = 3.58359e-05 (* 0.0454545 = 1.6289e-06 loss) | |
| I0407 16:26:52.013329 1004 solver.cpp:245] Train net output #39: loss/loss18 = 5.20324e-05 (* 0.0454545 = 2.36511e-06 loss) | |
| I0407 16:26:52.013344 1004 solver.cpp:245] Train net output #40: loss/loss19 = 3.97818e-05 (* 0.0454545 = 1.80826e-06 loss) | |
| I0407 16:26:52.013357 1004 solver.cpp:245] Train net output #41: loss/loss20 = 3.75946e-05 (* 0.0454545 = 1.70885e-06 loss) | |
| I0407 16:26:52.013371 1004 solver.cpp:245] Train net output #42: loss/loss21 = 4.34999e-05 (* 0.0454545 = 1.97727e-06 loss) | |
| I0407 16:26:52.013386 1004 solver.cpp:245] Train net output #43: loss/loss22 = 4.08842e-05 (* 0.0454545 = 1.85837e-06 loss) | |
| I0407 16:26:52.013397 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:26:52.013409 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000224287 | |
| I0407 16:26:52.013423 1004 sgd_solver.cpp:106] Iteration 55000, lr = 0.00089 | |
| I0407 16:27:31.455869 1004 solver.cpp:229] Iteration 55500, loss = 1.00531 | |
| I0407 16:27:31.456008 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:27:31.456029 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:27:31.456043 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:27:31.456054 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 16:27:31.456066 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 16:27:31.456079 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.25 | |
| I0407 16:27:31.456090 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 16:27:31.456104 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:27:31.456115 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:27:31.456126 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:27:31.456138 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:27:31.456149 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:27:31.456161 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:27:31.456176 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:27:31.456198 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:27:31.456223 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:27:31.456248 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:27:31.456264 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:27:31.456276 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:27:31.456289 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:27:31.456300 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:27:31.456311 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:27:31.456327 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.08606 (* 0.0454545 = 0.140276 loss) | |
| I0407 16:27:31.456341 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.44591 (* 0.0454545 = 0.156632 loss) | |
| I0407 16:27:31.456356 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.45476 (* 0.0454545 = 0.157035 loss) | |
| I0407 16:27:31.456369 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.43844 (* 0.0454545 = 0.156293 loss) | |
| I0407 16:27:31.456382 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.35869 (* 0.0454545 = 0.152668 loss) | |
| I0407 16:27:31.456396 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.19371 (* 0.0454545 = 0.145168 loss) | |
| I0407 16:27:31.456410 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.01736 (* 0.0454545 = 0.0462435 loss) | |
| I0407 16:27:31.456423 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.401925 (* 0.0454545 = 0.0182693 loss) | |
| I0407 16:27:31.456437 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0227486 (* 0.0454545 = 0.00103403 loss) | |
| I0407 16:27:31.456452 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0131879 (* 0.0454545 = 0.000599452 loss) | |
| I0407 16:27:31.456466 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000315961 (* 0.0454545 = 1.43619e-05 loss) | |
| I0407 16:27:31.456481 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000240978 (* 0.0454545 = 1.09535e-05 loss) | |
| I0407 16:27:31.456496 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000269233 (* 0.0454545 = 1.22379e-05 loss) | |
| I0407 16:27:31.456509 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000318943 (* 0.0454545 = 1.44974e-05 loss) | |
| I0407 16:27:31.456523 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000331226 (* 0.0454545 = 1.50557e-05 loss) | |
| I0407 16:27:31.456538 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000271847 (* 0.0454545 = 1.23567e-05 loss) | |
| I0407 16:27:31.456552 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000321267 (* 0.0454545 = 1.46031e-05 loss) | |
| I0407 16:27:31.456583 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000384803 (* 0.0454545 = 1.7491e-05 loss) | |
| I0407 16:27:31.456599 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000270437 (* 0.0454545 = 1.22926e-05 loss) | |
| I0407 16:27:31.456614 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000290505 (* 0.0454545 = 1.32048e-05 loss) | |
| I0407 16:27:31.456627 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000352643 (* 0.0454545 = 1.60292e-05 loss) | |
| I0407 16:27:31.456641 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000325903 (* 0.0454545 = 1.48138e-05 loss) | |
| I0407 16:27:31.456653 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:27:31.456665 1004 solver.cpp:245] Train net output #45: total_confidence = 1.14572e-05 | |
| I0407 16:27:31.456678 1004 sgd_solver.cpp:106] Iteration 55500, lr = 0.000889 | |
| I0407 16:28:10.338461 1004 solver.cpp:229] Iteration 56000, loss = 1.00169 | |
| I0407 16:28:10.338593 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:28:10.338614 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:28:10.338627 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 16:28:10.338639 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 16:28:10.338651 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 16:28:10.338665 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 16:28:10.338676 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 16:28:10.338687 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 16:28:10.338701 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.875 | |
| I0407 16:28:10.338711 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 16:28:10.338723 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:28:10.338735 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:28:10.338747 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:28:10.338757 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:28:10.338769 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:28:10.338786 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:28:10.338811 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:28:10.338834 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:28:10.338847 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:28:10.338860 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:28:10.338871 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:28:10.338882 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:28:10.338897 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.52363 (* 0.0454545 = 0.160165 loss) | |
| I0407 16:28:10.338912 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.62529 (* 0.0454545 = 0.164786 loss) | |
| I0407 16:28:10.338929 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.68932 (* 0.0454545 = 0.167696 loss) | |
| I0407 16:28:10.338943 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.67541 (* 0.0454545 = 0.167064 loss) | |
| I0407 16:28:10.338958 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.1831 (* 0.0454545 = 0.144687 loss) | |
| I0407 16:28:10.338971 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.94834 (* 0.0454545 = 0.134016 loss) | |
| I0407 16:28:10.338984 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.33819 (* 0.0454545 = 0.060827 loss) | |
| I0407 16:28:10.338999 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.918069 (* 0.0454545 = 0.0417304 loss) | |
| I0407 16:28:10.339012 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.816347 (* 0.0454545 = 0.0371067 loss) | |
| I0407 16:28:10.339025 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.540736 (* 0.0454545 = 0.0245789 loss) | |
| I0407 16:28:10.339040 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.00056046 (* 0.0454545 = 2.54754e-05 loss) | |
| I0407 16:28:10.339054 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000468117 (* 0.0454545 = 2.1278e-05 loss) | |
| I0407 16:28:10.339068 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000480243 (* 0.0454545 = 2.18292e-05 loss) | |
| I0407 16:28:10.339082 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000485687 (* 0.0454545 = 2.20767e-05 loss) | |
| I0407 16:28:10.339097 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000545504 (* 0.0454545 = 2.47956e-05 loss) | |
| I0407 16:28:10.339112 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000508973 (* 0.0454545 = 2.31351e-05 loss) | |
| I0407 16:28:10.339125 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000512874 (* 0.0454545 = 2.33125e-05 loss) | |
| I0407 16:28:10.339154 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000592046 (* 0.0454545 = 2.69112e-05 loss) | |
| I0407 16:28:10.339169 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000501436 (* 0.0454545 = 2.27925e-05 loss) | |
| I0407 16:28:10.339182 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000528495 (* 0.0454545 = 2.40225e-05 loss) | |
| I0407 16:28:10.339196 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000541296 (* 0.0454545 = 2.46044e-05 loss) | |
| I0407 16:28:10.339210 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000523615 (* 0.0454545 = 2.38007e-05 loss) | |
| I0407 16:28:10.339222 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:28:10.339234 1004 solver.cpp:245] Train net output #45: total_confidence = 5.1529e-06 | |
| I0407 16:28:10.339247 1004 sgd_solver.cpp:106] Iteration 56000, lr = 0.000888 | |
| I0407 16:28:49.105340 1004 solver.cpp:229] Iteration 56500, loss = 1.0033 | |
| I0407 16:28:49.105451 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:28:49.105471 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:28:49.105484 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:28:49.105495 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 16:28:49.105507 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 16:28:49.105520 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.625 | |
| I0407 16:28:49.105532 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 16:28:49.105543 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 16:28:49.105556 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:28:49.105567 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:28:49.105578 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:28:49.105589 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:28:49.105602 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:28:49.105612 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:28:49.105623 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:28:49.105635 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:28:49.105646 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:28:49.105659 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:28:49.105669 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:28:49.105681 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:28:49.105692 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:28:49.105703 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:28:49.105720 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.28381 (* 0.0454545 = 0.149264 loss) | |
| I0407 16:28:49.105733 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.66287 (* 0.0454545 = 0.166494 loss) | |
| I0407 16:28:49.105747 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.63789 (* 0.0454545 = 0.165358 loss) | |
| I0407 16:28:49.105762 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.50786 (* 0.0454545 = 0.159448 loss) | |
| I0407 16:28:49.105775 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.12333 (* 0.0454545 = 0.141969 loss) | |
| I0407 16:28:49.105789 1004 solver.cpp:245] Train net output #27: loss/loss06 = 1.56969 (* 0.0454545 = 0.0713494 loss) | |
| I0407 16:28:49.105803 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.17288 (* 0.0454545 = 0.0533127 loss) | |
| I0407 16:28:49.105816 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.740721 (* 0.0454545 = 0.0336691 loss) | |
| I0407 16:28:49.105830 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.338335 (* 0.0454545 = 0.0153788 loss) | |
| I0407 16:28:49.105844 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.016543 (* 0.0454545 = 0.000751956 loss) | |
| I0407 16:28:49.105859 1004 solver.cpp:245] Train net output #32: loss/loss11 = 2.84826e-05 (* 0.0454545 = 1.29466e-06 loss) | |
| I0407 16:28:49.105873 1004 solver.cpp:245] Train net output #33: loss/loss12 = 2.98869e-05 (* 0.0454545 = 1.3585e-06 loss) | |
| I0407 16:28:49.105887 1004 solver.cpp:245] Train net output #34: loss/loss13 = 3.05136e-05 (* 0.0454545 = 1.38698e-06 loss) | |
| I0407 16:28:49.105901 1004 solver.cpp:245] Train net output #35: loss/loss14 = 2.68805e-05 (* 0.0454545 = 1.22184e-06 loss) | |
| I0407 16:28:49.105916 1004 solver.cpp:245] Train net output #36: loss/loss15 = 3.05433e-05 (* 0.0454545 = 1.38833e-06 loss) | |
| I0407 16:28:49.105932 1004 solver.cpp:245] Train net output #37: loss/loss16 = 2.76291e-05 (* 0.0454545 = 1.25587e-06 loss) | |
| I0407 16:28:49.105947 1004 solver.cpp:245] Train net output #38: loss/loss17 = 2.98429e-05 (* 0.0454545 = 1.3565e-06 loss) | |
| I0407 16:28:49.105976 1004 solver.cpp:245] Train net output #39: loss/loss18 = 3.86332e-05 (* 0.0454545 = 1.75605e-06 loss) | |
| I0407 16:28:49.105993 1004 solver.cpp:245] Train net output #40: loss/loss19 = 2.74168e-05 (* 0.0454545 = 1.24622e-06 loss) | |
| I0407 16:28:49.106006 1004 solver.cpp:245] Train net output #41: loss/loss20 = 2.78266e-05 (* 0.0454545 = 1.26484e-06 loss) | |
| I0407 16:28:49.106020 1004 solver.cpp:245] Train net output #42: loss/loss21 = 2.98206e-05 (* 0.0454545 = 1.35548e-06 loss) | |
| I0407 16:28:49.106034 1004 solver.cpp:245] Train net output #43: loss/loss22 = 3.20934e-05 (* 0.0454545 = 1.45879e-06 loss) | |
| I0407 16:28:49.106046 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:28:49.106057 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000127106 | |
| I0407 16:28:49.106071 1004 sgd_solver.cpp:106] Iteration 56500, lr = 0.000887 | |
| I0407 16:29:28.580324 1004 solver.cpp:229] Iteration 57000, loss = 1.00024 | |
| I0407 16:29:28.580442 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:29:28.580471 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:29:28.580497 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:29:28.580519 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 16:29:28.580541 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 16:29:28.580566 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 16:29:28.580590 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 16:29:28.580611 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 16:29:28.580631 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.875 | |
| I0407 16:29:28.580648 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 16:29:28.580669 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:29:28.580690 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:29:28.580713 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:29:28.580734 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:29:28.580754 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:29:28.580775 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:29:28.580796 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:29:28.580817 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:29:28.580838 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:29:28.580859 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:29:28.580883 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:29:28.580906 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:29:28.580940 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.02612 (* 0.0454545 = 0.137551 loss) | |
| I0407 16:29:28.580966 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.22721 (* 0.0454545 = 0.146691 loss) | |
| I0407 16:29:28.580992 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.73001 (* 0.0454545 = 0.169546 loss) | |
| I0407 16:29:28.581018 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.83543 (* 0.0454545 = 0.174338 loss) | |
| I0407 16:29:28.581045 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.28597 (* 0.0454545 = 0.149362 loss) | |
| I0407 16:29:28.581070 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.7924 (* 0.0454545 = 0.126927 loss) | |
| I0407 16:29:28.581096 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.904208 (* 0.0454545 = 0.0411004 loss) | |
| I0407 16:29:28.581121 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.566815 (* 0.0454545 = 0.0257643 loss) | |
| I0407 16:29:28.581147 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.605054 (* 0.0454545 = 0.0275025 loss) | |
| I0407 16:29:28.581172 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.382393 (* 0.0454545 = 0.0173815 loss) | |
| I0407 16:29:28.581198 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000185342 (* 0.0454545 = 8.42463e-06 loss) | |
| I0407 16:29:28.581225 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000146347 (* 0.0454545 = 6.65215e-06 loss) | |
| I0407 16:29:28.581251 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000168781 (* 0.0454545 = 7.67187e-06 loss) | |
| I0407 16:29:28.581277 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000179174 (* 0.0454545 = 8.14426e-06 loss) | |
| I0407 16:29:28.581302 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000197081 (* 0.0454545 = 8.9582e-06 loss) | |
| I0407 16:29:28.581329 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000163694 (* 0.0454545 = 7.44064e-06 loss) | |
| I0407 16:29:28.581356 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000178892 (* 0.0454545 = 8.13148e-06 loss) | |
| I0407 16:29:28.581403 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000219929 (* 0.0454545 = 9.99679e-06 loss) | |
| I0407 16:29:28.581430 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000158854 (* 0.0454545 = 7.22065e-06 loss) | |
| I0407 16:29:28.581461 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000182424 (* 0.0454545 = 8.29201e-06 loss) | |
| I0407 16:29:28.581490 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000205847 (* 0.0454545 = 9.3567e-06 loss) | |
| I0407 16:29:28.581516 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000160419 (* 0.0454545 = 7.29179e-06 loss) | |
| I0407 16:29:28.581538 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:29:28.581559 1004 solver.cpp:245] Train net output #45: total_confidence = 3.43692e-05 | |
| I0407 16:29:28.581583 1004 sgd_solver.cpp:106] Iteration 57000, lr = 0.000886 | |
| I0407 16:30:07.699607 1004 solver.cpp:229] Iteration 57500, loss = 1.00883 | |
| I0407 16:30:07.699751 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.25 | |
| I0407 16:30:07.699779 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:30:07.699800 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:30:07.699823 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 16:30:07.699846 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 16:30:07.699867 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.25 | |
| I0407 16:30:07.699887 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.5625 | |
| I0407 16:30:07.699908 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 16:30:07.699935 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:30:07.699956 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:30:07.699981 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:30:07.700002 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:30:07.700023 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:30:07.700044 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:30:07.700065 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:30:07.700086 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:30:07.700108 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:30:07.700129 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:30:07.700150 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:30:07.700170 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:30:07.700191 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:30:07.700212 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:30:07.700238 1004 solver.cpp:245] Train net output #22: loss/loss01 = 2.8404 (* 0.0454545 = 0.129109 loss) | |
| I0407 16:30:07.700265 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.36854 (* 0.0454545 = 0.153116 loss) | |
| I0407 16:30:07.700291 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.15903 (* 0.0454545 = 0.143592 loss) | |
| I0407 16:30:07.700316 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.1245 (* 0.0454545 = 0.142023 loss) | |
| I0407 16:30:07.700341 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.36957 (* 0.0454545 = 0.153162 loss) | |
| I0407 16:30:07.700367 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.96775 (* 0.0454545 = 0.134898 loss) | |
| I0407 16:30:07.700393 1004 solver.cpp:245] Train net output #28: loss/loss07 = 2.12031 (* 0.0454545 = 0.0963778 loss) | |
| I0407 16:30:07.700418 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.0588772 (* 0.0454545 = 0.00267624 loss) | |
| I0407 16:30:07.700444 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0115167 (* 0.0454545 = 0.000523488 loss) | |
| I0407 16:30:07.700470 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.00598781 (* 0.0454545 = 0.000272173 loss) | |
| I0407 16:30:07.700496 1004 solver.cpp:245] Train net output #32: loss/loss11 = 2.36314e-05 (* 0.0454545 = 1.07415e-06 loss) | |
| I0407 16:30:07.700528 1004 solver.cpp:245] Train net output #33: loss/loss12 = 1.903e-05 (* 0.0454545 = 8.64998e-07 loss) | |
| I0407 16:30:07.700558 1004 solver.cpp:245] Train net output #34: loss/loss13 = 1.89554e-05 (* 0.0454545 = 8.61609e-07 loss) | |
| I0407 16:30:07.700585 1004 solver.cpp:245] Train net output #35: loss/loss14 = 1.97229e-05 (* 0.0454545 = 8.96498e-07 loss) | |
| I0407 16:30:07.700613 1004 solver.cpp:245] Train net output #36: loss/loss15 = 2.22379e-05 (* 0.0454545 = 1.01081e-06 loss) | |
| I0407 16:30:07.700639 1004 solver.cpp:245] Train net output #37: loss/loss16 = 1.98571e-05 (* 0.0454545 = 9.02596e-07 loss) | |
| I0407 16:30:07.700665 1004 solver.cpp:245] Train net output #38: loss/loss17 = 2.11946e-05 (* 0.0454545 = 9.63392e-07 loss) | |
| I0407 16:30:07.700714 1004 solver.cpp:245] Train net output #39: loss/loss18 = 2.29681e-05 (* 0.0454545 = 1.044e-06 loss) | |
| I0407 16:30:07.700743 1004 solver.cpp:245] Train net output #40: loss/loss19 = 1.90076e-05 (* 0.0454545 = 8.63981e-07 loss) | |
| I0407 16:30:07.700775 1004 solver.cpp:245] Train net output #41: loss/loss20 = 1.78154e-05 (* 0.0454545 = 8.09789e-07 loss) | |
| I0407 16:30:07.700803 1004 solver.cpp:245] Train net output #42: loss/loss21 = 2.08854e-05 (* 0.0454545 = 9.49335e-07 loss) | |
| I0407 16:30:07.700830 1004 solver.cpp:245] Train net output #43: loss/loss22 = 1.90076e-05 (* 0.0454545 = 8.63982e-07 loss) | |
| I0407 16:30:07.700852 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:30:07.700873 1004 solver.cpp:245] Train net output #45: total_confidence = 8.59093e-05 | |
| I0407 16:30:07.700896 1004 sgd_solver.cpp:106] Iteration 57500, lr = 0.000885 | |
| I0407 16:30:46.870340 1004 solver.cpp:229] Iteration 58000, loss = 1.00731 | |
| I0407 16:30:46.870499 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:30:46.870520 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:30:46.870533 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:30:46.870545 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 16:30:46.870558 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 16:30:46.870569 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 16:30:46.870581 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 16:30:46.870594 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 16:30:46.870605 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:30:46.870616 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:30:46.870628 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:30:46.870640 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:30:46.870651 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:30:46.870663 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:30:46.870676 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:30:46.870687 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:30:46.870698 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:30:46.870710 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:30:46.870721 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:30:46.870733 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:30:46.870744 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:30:46.870756 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:30:46.870772 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.13558 (* 0.0454545 = 0.142526 loss) | |
| I0407 16:30:46.870787 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.42346 (* 0.0454545 = 0.155612 loss) | |
| I0407 16:30:46.870801 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.67481 (* 0.0454545 = 0.167037 loss) | |
| I0407 16:30:46.870815 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.30428 (* 0.0454545 = 0.150195 loss) | |
| I0407 16:30:46.870829 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.18798 (* 0.0454545 = 0.144908 loss) | |
| I0407 16:30:46.870842 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.6174 (* 0.0454545 = 0.118973 loss) | |
| I0407 16:30:46.870857 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.34449 (* 0.0454545 = 0.061113 loss) | |
| I0407 16:30:46.870870 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.680545 (* 0.0454545 = 0.0309339 loss) | |
| I0407 16:30:46.870884 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.00642572 (* 0.0454545 = 0.000292078 loss) | |
| I0407 16:30:46.870898 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0028391 (* 0.0454545 = 0.00012905 loss) | |
| I0407 16:30:46.870913 1004 solver.cpp:245] Train net output #32: loss/loss11 = 3.99705e-05 (* 0.0454545 = 1.81684e-06 loss) | |
| I0407 16:30:46.870930 1004 solver.cpp:245] Train net output #33: loss/loss12 = 3.55021e-05 (* 0.0454545 = 1.61373e-06 loss) | |
| I0407 16:30:46.870944 1004 solver.cpp:245] Train net output #34: loss/loss13 = 3.43351e-05 (* 0.0454545 = 1.56068e-06 loss) | |
| I0407 16:30:46.870959 1004 solver.cpp:245] Train net output #35: loss/loss14 = 3.39848e-05 (* 0.0454545 = 1.54477e-06 loss) | |
| I0407 16:30:46.870973 1004 solver.cpp:245] Train net output #36: loss/loss15 = 4.49837e-05 (* 0.0454545 = 2.04472e-06 loss) | |
| I0407 16:30:46.870987 1004 solver.cpp:245] Train net output #37: loss/loss16 = 3.32844e-05 (* 0.0454545 = 1.51293e-06 loss) | |
| I0407 16:30:46.871001 1004 solver.cpp:245] Train net output #38: loss/loss17 = 4.38734e-05 (* 0.0454545 = 1.99425e-06 loss) | |
| I0407 16:30:46.871028 1004 solver.cpp:245] Train net output #39: loss/loss18 = 4.7552e-05 (* 0.0454545 = 2.16145e-06 loss) | |
| I0407 16:30:46.871044 1004 solver.cpp:245] Train net output #40: loss/loss19 = 3.70895e-05 (* 0.0454545 = 1.68589e-06 loss) | |
| I0407 16:30:46.871058 1004 solver.cpp:245] Train net output #41: loss/loss20 = 3.51144e-05 (* 0.0454545 = 1.59611e-06 loss) | |
| I0407 16:30:46.871073 1004 solver.cpp:245] Train net output #42: loss/loss21 = 4.35445e-05 (* 0.0454545 = 1.9793e-06 loss) | |
| I0407 16:30:46.871086 1004 solver.cpp:245] Train net output #43: loss/loss22 = 4.04703e-05 (* 0.0454545 = 1.83956e-06 loss) | |
| I0407 16:30:46.871098 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:30:46.871110 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000156689 | |
| I0407 16:30:46.871124 1004 sgd_solver.cpp:106] Iteration 58000, lr = 0.000884 | |
| I0407 16:31:26.023600 1004 solver.cpp:229] Iteration 58500, loss = 1.00044 | |
| I0407 16:31:26.023744 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 16:31:26.023772 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:31:26.023797 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:31:26.023818 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 16:31:26.023841 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 16:31:26.023861 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5625 | |
| I0407 16:31:26.023886 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 16:31:26.023910 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 16:31:26.023934 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:31:26.023957 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:31:26.023977 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:31:26.023998 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:31:26.024019 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:31:26.024040 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:31:26.024062 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:31:26.024083 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:31:26.024103 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:31:26.024124 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:31:26.024147 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:31:26.024166 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:31:26.024188 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:31:26.024209 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:31:26.024235 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.26596 (* 0.0454545 = 0.148453 loss) | |
| I0407 16:31:26.024266 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.38383 (* 0.0454545 = 0.153811 loss) | |
| I0407 16:31:26.024296 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.59314 (* 0.0454545 = 0.163325 loss) | |
| I0407 16:31:26.024322 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.37561 (* 0.0454545 = 0.153437 loss) | |
| I0407 16:31:26.024348 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.31404 (* 0.0454545 = 0.150638 loss) | |
| I0407 16:31:26.024372 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.03586 (* 0.0454545 = 0.0925392 loss) | |
| I0407 16:31:26.024399 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.32577 (* 0.0454545 = 0.0602621 loss) | |
| I0407 16:31:26.024425 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.0768398 (* 0.0454545 = 0.00349272 loss) | |
| I0407 16:31:26.024451 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0175713 (* 0.0454545 = 0.000798694 loss) | |
| I0407 16:31:26.024477 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.00583136 (* 0.0454545 = 0.000265062 loss) | |
| I0407 16:31:26.024503 1004 solver.cpp:245] Train net output #32: loss/loss11 = 6.08722e-06 (* 0.0454545 = 2.76692e-07 loss) | |
| I0407 16:31:26.024530 1004 solver.cpp:245] Train net output #33: loss/loss12 = 6.33311e-06 (* 0.0454545 = 2.87869e-07 loss) | |
| I0407 16:31:26.024556 1004 solver.cpp:245] Train net output #34: loss/loss13 = 5.24528e-06 (* 0.0454545 = 2.38422e-07 loss) | |
| I0407 16:31:26.024583 1004 solver.cpp:245] Train net output #35: loss/loss14 = 5.99037e-06 (* 0.0454545 = 2.72289e-07 loss) | |
| I0407 16:31:26.024610 1004 solver.cpp:245] Train net output #36: loss/loss15 = 7.36878e-06 (* 0.0454545 = 3.34944e-07 loss) | |
| I0407 16:31:26.024636 1004 solver.cpp:245] Train net output #37: loss/loss16 = 5.84879e-06 (* 0.0454545 = 2.65854e-07 loss) | |
| I0407 16:31:26.024662 1004 solver.cpp:245] Train net output #38: loss/loss17 = 6.25114e-06 (* 0.0454545 = 2.84143e-07 loss) | |
| I0407 16:31:26.024710 1004 solver.cpp:245] Train net output #39: loss/loss18 = 7.08563e-06 (* 0.0454545 = 3.22074e-07 loss) | |
| I0407 16:31:26.024739 1004 solver.cpp:245] Train net output #40: loss/loss19 = 5.55822e-06 (* 0.0454545 = 2.52646e-07 loss) | |
| I0407 16:31:26.024770 1004 solver.cpp:245] Train net output #41: loss/loss20 = 6.19155e-06 (* 0.0454545 = 2.81434e-07 loss) | |
| I0407 16:31:26.024797 1004 solver.cpp:245] Train net output #42: loss/loss21 = 6.22133e-06 (* 0.0454545 = 2.82788e-07 loss) | |
| I0407 16:31:26.024824 1004 solver.cpp:245] Train net output #43: loss/loss22 = 5.44645e-06 (* 0.0454545 = 2.47566e-07 loss) | |
| I0407 16:31:26.024845 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:31:26.024866 1004 solver.cpp:245] Train net output #45: total_confidence = 9.33228e-05 | |
| I0407 16:31:26.024889 1004 sgd_solver.cpp:106] Iteration 58500, lr = 0.000883 | |
| I0407 16:32:05.512015 1004 solver.cpp:229] Iteration 59000, loss = 1.00323 | |
| I0407 16:32:05.512145 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:32:05.512173 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:32:05.512194 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:32:05.512215 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 16:32:05.512236 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 16:32:05.512259 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 16:32:05.512279 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 16:32:05.512300 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 16:32:05.512322 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:32:05.512343 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:32:05.512363 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:32:05.512383 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:32:05.512406 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:32:05.512429 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:32:05.512450 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:32:05.512472 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:32:05.512495 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:32:05.512514 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:32:05.512536 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:32:05.512555 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:32:05.512576 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:32:05.512598 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:32:05.512625 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.6085 (* 0.0454545 = 0.164023 loss) | |
| I0407 16:32:05.512652 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.71402 (* 0.0454545 = 0.168819 loss) | |
| I0407 16:32:05.512678 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.69942 (* 0.0454545 = 0.168156 loss) | |
| I0407 16:32:05.512704 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.86682 (* 0.0454545 = 0.175765 loss) | |
| I0407 16:32:05.512729 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.55827 (* 0.0454545 = 0.16174 loss) | |
| I0407 16:32:05.512754 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.55688 (* 0.0454545 = 0.116222 loss) | |
| I0407 16:32:05.512780 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.989404 (* 0.0454545 = 0.0449729 loss) | |
| I0407 16:32:05.512805 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.609229 (* 0.0454545 = 0.0276922 loss) | |
| I0407 16:32:05.512831 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0357187 (* 0.0454545 = 0.00162358 loss) | |
| I0407 16:32:05.512857 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0151099 (* 0.0454545 = 0.000686812 loss) | |
| I0407 16:32:05.512883 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000596786 (* 0.0454545 = 2.71266e-05 loss) | |
| I0407 16:32:05.512909 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000556717 (* 0.0454545 = 2.53053e-05 loss) | |
| I0407 16:32:05.512936 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000538369 (* 0.0454545 = 2.44713e-05 loss) | |
| I0407 16:32:05.512961 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000611048 (* 0.0454545 = 2.77749e-05 loss) | |
| I0407 16:32:05.512989 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000672746 (* 0.0454545 = 3.05794e-05 loss) | |
| I0407 16:32:05.513015 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000533246 (* 0.0454545 = 2.42385e-05 loss) | |
| I0407 16:32:05.513041 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000679693 (* 0.0454545 = 3.08951e-05 loss) | |
| I0407 16:32:05.513090 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000718325 (* 0.0454545 = 3.26511e-05 loss) | |
| I0407 16:32:05.513118 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000581582 (* 0.0454545 = 2.64355e-05 loss) | |
| I0407 16:32:05.513144 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000546116 (* 0.0454545 = 2.48235e-05 loss) | |
| I0407 16:32:05.513176 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000664079 (* 0.0454545 = 3.01854e-05 loss) | |
| I0407 16:32:05.513208 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000590455 (* 0.0454545 = 2.68389e-05 loss) | |
| I0407 16:32:05.513231 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:32:05.513253 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000102258 | |
| I0407 16:32:05.513276 1004 sgd_solver.cpp:106] Iteration 59000, lr = 0.000882 | |
| I0407 16:32:45.062306 1004 solver.cpp:229] Iteration 59500, loss = 0.99565 | |
| I0407 16:32:45.062427 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:32:45.062454 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.125 | |
| I0407 16:32:45.062479 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 16:32:45.062500 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 16:32:45.062522 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0 | |
| I0407 16:32:45.062544 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.125 | |
| I0407 16:32:45.062566 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 16:32:45.062592 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 16:32:45.062615 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:32:45.062638 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:32:45.062659 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:32:45.062680 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:32:45.062700 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:32:45.062722 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:32:45.062743 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:32:45.062763 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:32:45.062784 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:32:45.062805 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:32:45.062826 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:32:45.062849 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:32:45.062870 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:32:45.062890 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:32:45.062921 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.66104 (* 0.0454545 = 0.166411 loss) | |
| I0407 16:32:45.062948 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.879 (* 0.0454545 = 0.176318 loss) | |
| I0407 16:32:45.062975 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.84277 (* 0.0454545 = 0.174671 loss) | |
| I0407 16:32:45.063001 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.76171 (* 0.0454545 = 0.170987 loss) | |
| I0407 16:32:45.063030 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.99943 (* 0.0454545 = 0.181792 loss) | |
| I0407 16:32:45.063055 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.7508 (* 0.0454545 = 0.170491 loss) | |
| I0407 16:32:45.063081 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.26592 (* 0.0454545 = 0.0575419 loss) | |
| I0407 16:32:45.063105 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.131681 (* 0.0454545 = 0.00598548 loss) | |
| I0407 16:32:45.063132 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0325557 (* 0.0454545 = 0.0014798 loss) | |
| I0407 16:32:45.063156 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0127636 (* 0.0454545 = 0.000580166 loss) | |
| I0407 16:32:45.063184 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000329473 (* 0.0454545 = 1.4976e-05 loss) | |
| I0407 16:32:45.063210 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000287882 (* 0.0454545 = 1.30856e-05 loss) | |
| I0407 16:32:45.063235 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.00031093 (* 0.0454545 = 1.41332e-05 loss) | |
| I0407 16:32:45.063261 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000337916 (* 0.0454545 = 1.53598e-05 loss) | |
| I0407 16:32:45.063287 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000340665 (* 0.0454545 = 1.54848e-05 loss) | |
| I0407 16:32:45.063313 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000309907 (* 0.0454545 = 1.40867e-05 loss) | |
| I0407 16:32:45.063355 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.00036359 (* 0.0454545 = 1.65268e-05 loss) | |
| I0407 16:32:45.063406 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000386579 (* 0.0454545 = 1.75718e-05 loss) | |
| I0407 16:32:45.063438 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00031549 (* 0.0454545 = 1.43404e-05 loss) | |
| I0407 16:32:45.063467 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000312917 (* 0.0454545 = 1.42235e-05 loss) | |
| I0407 16:32:45.063493 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00038363 (* 0.0454545 = 1.74377e-05 loss) | |
| I0407 16:32:45.063520 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000316337 (* 0.0454545 = 1.4379e-05 loss) | |
| I0407 16:32:45.063544 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:32:45.063565 1004 solver.cpp:245] Train net output #45: total_confidence = 1.87702e-06 | |
| I0407 16:32:45.063588 1004 sgd_solver.cpp:106] Iteration 59500, lr = 0.000881 | |
| I0407 16:33:23.693553 1004 solver.cpp:338] Iteration 60000, Testing net (#0) | |
| I0407 16:33:31.623431 1004 solver.cpp:393] Test loss: 0.894539 | |
| I0407 16:33:31.623479 1004 solver.cpp:406] Test net output #0: loss/accuracy01 = 0.362 | |
| I0407 16:33:31.623497 1004 solver.cpp:406] Test net output #1: loss/accuracy02 = 0.098 | |
| I0407 16:33:31.623510 1004 solver.cpp:406] Test net output #2: loss/accuracy03 = 0.08 | |
| I0407 16:33:31.623522 1004 solver.cpp:406] Test net output #3: loss/accuracy04 = 0.079 | |
| I0407 16:33:31.623534 1004 solver.cpp:406] Test net output #4: loss/accuracy05 = 0.202 | |
| I0407 16:33:31.623546 1004 solver.cpp:406] Test net output #5: loss/accuracy06 = 0.496 | |
| I0407 16:33:31.623558 1004 solver.cpp:406] Test net output #6: loss/accuracy07 = 0.894 | |
| I0407 16:33:31.623569 1004 solver.cpp:406] Test net output #7: loss/accuracy08 = 0.97 | |
| I0407 16:33:31.623580 1004 solver.cpp:406] Test net output #8: loss/accuracy09 = 0.995 | |
| I0407 16:33:31.623591 1004 solver.cpp:406] Test net output #9: loss/accuracy10 = 0.998 | |
| I0407 16:33:31.623602 1004 solver.cpp:406] Test net output #10: loss/accuracy11 = 1 | |
| I0407 16:33:31.623615 1004 solver.cpp:406] Test net output #11: loss/accuracy12 = 1 | |
| I0407 16:33:31.623625 1004 solver.cpp:406] Test net output #12: loss/accuracy13 = 1 | |
| I0407 16:33:31.623636 1004 solver.cpp:406] Test net output #13: loss/accuracy14 = 1 | |
| I0407 16:33:31.623647 1004 solver.cpp:406] Test net output #14: loss/accuracy15 = 1 | |
| I0407 16:33:31.623658 1004 solver.cpp:406] Test net output #15: loss/accuracy16 = 1 | |
| I0407 16:33:31.623669 1004 solver.cpp:406] Test net output #16: loss/accuracy17 = 1 | |
| I0407 16:33:31.623680 1004 solver.cpp:406] Test net output #17: loss/accuracy18 = 1 | |
| I0407 16:33:31.623692 1004 solver.cpp:406] Test net output #18: loss/accuracy19 = 1 | |
| I0407 16:33:31.623703 1004 solver.cpp:406] Test net output #19: loss/accuracy20 = 1 | |
| I0407 16:33:31.623713 1004 solver.cpp:406] Test net output #20: loss/accuracy21 = 1 | |
| I0407 16:33:31.623724 1004 solver.cpp:406] Test net output #21: loss/accuracy22 = 1 | |
| I0407 16:33:31.623739 1004 solver.cpp:406] Test net output #22: loss/loss01 = 3.01864 (* 0.0454545 = 0.137211 loss) | |
| I0407 16:33:31.623754 1004 solver.cpp:406] Test net output #23: loss/loss02 = 3.28682 (* 0.0454545 = 0.149401 loss) | |
| I0407 16:33:31.623769 1004 solver.cpp:406] Test net output #24: loss/loss03 = 3.36936 (* 0.0454545 = 0.153153 loss) | |
| I0407 16:33:31.623781 1004 solver.cpp:406] Test net output #25: loss/loss04 = 3.33659 (* 0.0454545 = 0.151663 loss) | |
| I0407 16:33:31.623795 1004 solver.cpp:406] Test net output #26: loss/loss05 = 3.26165 (* 0.0454545 = 0.148257 loss) | |
| I0407 16:33:31.623808 1004 solver.cpp:406] Test net output #27: loss/loss06 = 2.27936 (* 0.0454545 = 0.103607 loss) | |
| I0407 16:33:31.623821 1004 solver.cpp:406] Test net output #28: loss/loss07 = 0.744315 (* 0.0454545 = 0.0338325 loss) | |
| I0407 16:33:31.623834 1004 solver.cpp:406] Test net output #29: loss/loss08 = 0.271226 (* 0.0454545 = 0.0123285 loss) | |
| I0407 16:33:31.623848 1004 solver.cpp:406] Test net output #30: loss/loss09 = 0.0665362 (* 0.0454545 = 0.00302437 loss) | |
| I0407 16:33:31.623862 1004 solver.cpp:406] Test net output #31: loss/loss10 = 0.0352758 (* 0.0454545 = 0.00160345 loss) | |
| I0407 16:33:31.623877 1004 solver.cpp:406] Test net output #32: loss/loss11 = 0.000898783 (* 0.0454545 = 4.08538e-05 loss) | |
| I0407 16:33:31.623890 1004 solver.cpp:406] Test net output #33: loss/loss12 = 0.000833551 (* 0.0454545 = 3.78887e-05 loss) | |
| I0407 16:33:31.623904 1004 solver.cpp:406] Test net output #34: loss/loss13 = 0.000823597 (* 0.0454545 = 3.74362e-05 loss) | |
| I0407 16:33:31.623920 1004 solver.cpp:406] Test net output #35: loss/loss14 = 0.000817377 (* 0.0454545 = 3.71535e-05 loss) | |
| I0407 16:33:31.623934 1004 solver.cpp:406] Test net output #36: loss/loss15 = 0.000821194 (* 0.0454545 = 3.7327e-05 loss) | |
| I0407 16:33:31.623949 1004 solver.cpp:406] Test net output #37: loss/loss16 = 0.000834321 (* 0.0454545 = 3.79237e-05 loss) | |
| I0407 16:33:31.623962 1004 solver.cpp:406] Test net output #38: loss/loss17 = 0.000845954 (* 0.0454545 = 3.84525e-05 loss) | |
| I0407 16:33:31.624011 1004 solver.cpp:406] Test net output #39: loss/loss18 = 0.000924435 (* 0.0454545 = 4.20198e-05 loss) | |
| I0407 16:33:31.624027 1004 solver.cpp:406] Test net output #40: loss/loss19 = 0.000786688 (* 0.0454545 = 3.57585e-05 loss) | |
| I0407 16:33:31.624039 1004 solver.cpp:406] Test net output #41: loss/loss20 = 0.000807159 (* 0.0454545 = 3.6689e-05 loss) | |
| I0407 16:33:31.624053 1004 solver.cpp:406] Test net output #42: loss/loss21 = 0.000855601 (* 0.0454545 = 3.8891e-05 loss) | |
| I0407 16:33:31.624068 1004 solver.cpp:406] Test net output #43: loss/loss22 = 0.000829854 (* 0.0454545 = 3.77206e-05 loss) | |
| I0407 16:33:31.624079 1004 solver.cpp:406] Test net output #44: total_accuracy = 0 | |
| I0407 16:33:31.624090 1004 solver.cpp:406] Test net output #45: total_confidence = 0.000155933 | |
| I0407 16:33:31.645632 1004 solver.cpp:229] Iteration 60000, loss = 0.99382 | |
| I0407 16:33:31.645668 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:33:31.645685 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:33:31.645701 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.1875 | |
| I0407 16:33:31.645714 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 16:33:31.645725 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 16:33:31.645738 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 16:33:31.645750 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 16:33:31.645761 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:33:31.645772 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:33:31.645783 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:33:31.645795 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:33:31.645807 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:33:31.645817 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:33:31.645829 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:33:31.645840 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:33:31.645851 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:33:31.645862 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:33:31.645874 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:33:31.645885 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:33:31.645896 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:33:31.645907 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:33:31.645918 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:33:31.645932 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.19695 (* 0.0454545 = 0.145316 loss) | |
| I0407 16:33:31.645946 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.43108 (* 0.0454545 = 0.155958 loss) | |
| I0407 16:33:31.645961 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.38937 (* 0.0454545 = 0.154062 loss) | |
| I0407 16:33:31.645973 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.53885 (* 0.0454545 = 0.160857 loss) | |
| I0407 16:33:31.645987 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.17362 (* 0.0454545 = 0.144256 loss) | |
| I0407 16:33:31.646001 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.58118 (* 0.0454545 = 0.117326 loss) | |
| I0407 16:33:31.646014 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.989236 (* 0.0454545 = 0.0449653 loss) | |
| I0407 16:33:31.646028 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.540277 (* 0.0454545 = 0.024558 loss) | |
| I0407 16:33:31.646042 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0304486 (* 0.0454545 = 0.00138403 loss) | |
| I0407 16:33:31.646056 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0117331 (* 0.0454545 = 0.000533321 loss) | |
| I0407 16:33:31.646090 1004 solver.cpp:245] Train net output #32: loss/loss11 = 2.79336e-05 (* 0.0454545 = 1.26971e-06 loss) | |
| I0407 16:33:31.646106 1004 solver.cpp:245] Train net output #33: loss/loss12 = 2.56163e-05 (* 0.0454545 = 1.16438e-06 loss) | |
| I0407 16:33:31.646119 1004 solver.cpp:245] Train net output #34: loss/loss13 = 2.45061e-05 (* 0.0454545 = 1.11391e-06 loss) | |
| I0407 16:33:31.646133 1004 solver.cpp:245] Train net output #35: loss/loss14 = 2.61827e-05 (* 0.0454545 = 1.19012e-06 loss) | |
| I0407 16:33:31.646147 1004 solver.cpp:245] Train net output #36: loss/loss15 = 2.74531e-05 (* 0.0454545 = 1.24787e-06 loss) | |
| I0407 16:33:31.646162 1004 solver.cpp:245] Train net output #37: loss/loss16 = 2.5147e-05 (* 0.0454545 = 1.14304e-06 loss) | |
| I0407 16:33:31.646175 1004 solver.cpp:245] Train net output #38: loss/loss17 = 2.58772e-05 (* 0.0454545 = 1.17623e-06 loss) | |
| I0407 16:33:31.646188 1004 solver.cpp:245] Train net output #39: loss/loss18 = 3.15067e-05 (* 0.0454545 = 1.43212e-06 loss) | |
| I0407 16:33:31.646203 1004 solver.cpp:245] Train net output #40: loss/loss19 = 2.45621e-05 (* 0.0454545 = 1.11646e-06 loss) | |
| I0407 16:33:31.646216 1004 solver.cpp:245] Train net output #41: loss/loss20 = 2.79749e-05 (* 0.0454545 = 1.27159e-06 loss) | |
| I0407 16:33:31.646230 1004 solver.cpp:245] Train net output #42: loss/loss21 = 2.86603e-05 (* 0.0454545 = 1.30274e-06 loss) | |
| I0407 16:33:31.646244 1004 solver.cpp:245] Train net output #43: loss/loss22 = 2.66595e-05 (* 0.0454545 = 1.21179e-06 loss) | |
| I0407 16:33:31.646255 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:33:31.646267 1004 solver.cpp:245] Train net output #45: total_confidence = 4.26584e-05 | |
| I0407 16:33:31.646281 1004 sgd_solver.cpp:106] Iteration 60000, lr = 0.00088 | |
| I0407 16:34:09.892370 1004 solver.cpp:229] Iteration 60500, loss = 0.989298 | |
| I0407 16:34:09.892482 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:34:09.892501 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:34:09.892514 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:34:09.892526 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 16:34:09.892539 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.3125 | |
| I0407 16:34:09.892550 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5625 | |
| I0407 16:34:09.892563 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 16:34:09.892575 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:34:09.892586 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:34:09.892597 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:34:09.892609 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:34:09.892621 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:34:09.892632 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:34:09.892643 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:34:09.892654 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:34:09.892665 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:34:09.892676 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:34:09.892688 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:34:09.892699 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:34:09.892710 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:34:09.892722 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:34:09.892734 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:34:09.892750 1004 solver.cpp:245] Train net output #22: loss/loss01 = 2.90085 (* 0.0454545 = 0.131857 loss) | |
| I0407 16:34:09.892763 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.30321 (* 0.0454545 = 0.150146 loss) | |
| I0407 16:34:09.892777 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.2366 (* 0.0454545 = 0.147118 loss) | |
| I0407 16:34:09.892791 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.03448 (* 0.0454545 = 0.137931 loss) | |
| I0407 16:34:09.892805 1004 solver.cpp:245] Train net output #26: loss/loss05 = 2.74852 (* 0.0454545 = 0.124933 loss) | |
| I0407 16:34:09.892820 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.08312 (* 0.0454545 = 0.0946872 loss) | |
| I0407 16:34:09.892834 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.972345 (* 0.0454545 = 0.0441975 loss) | |
| I0407 16:34:09.892848 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.298147 (* 0.0454545 = 0.0135521 loss) | |
| I0407 16:34:09.892863 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0138037 (* 0.0454545 = 0.000627442 loss) | |
| I0407 16:34:09.892876 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.00437982 (* 0.0454545 = 0.000199083 loss) | |
| I0407 16:34:09.892891 1004 solver.cpp:245] Train net output #32: loss/loss11 = 1.05056e-05 (* 0.0454545 = 4.77529e-07 loss) | |
| I0407 16:34:09.892905 1004 solver.cpp:245] Train net output #33: loss/loss12 = 1.04609e-05 (* 0.0454545 = 4.75497e-07 loss) | |
| I0407 16:34:09.892921 1004 solver.cpp:245] Train net output #34: loss/loss13 = 9.25388e-06 (* 0.0454545 = 4.20631e-07 loss) | |
| I0407 16:34:09.892936 1004 solver.cpp:245] Train net output #35: loss/loss14 = 9.79038e-06 (* 0.0454545 = 4.45017e-07 loss) | |
| I0407 16:34:09.892951 1004 solver.cpp:245] Train net output #36: loss/loss15 = 1.02598e-05 (* 0.0454545 = 4.66354e-07 loss) | |
| I0407 16:34:09.892964 1004 solver.cpp:245] Train net output #37: loss/loss16 = 9.3284e-06 (* 0.0454545 = 4.24018e-07 loss) | |
| I0407 16:34:09.892978 1004 solver.cpp:245] Train net output #38: loss/loss17 = 1.03939e-05 (* 0.0454545 = 4.72451e-07 loss) | |
| I0407 16:34:09.893010 1004 solver.cpp:245] Train net output #39: loss/loss18 = 1.13924e-05 (* 0.0454545 = 5.17836e-07 loss) | |
| I0407 16:34:09.893025 1004 solver.cpp:245] Train net output #40: loss/loss19 = 9.71588e-06 (* 0.0454545 = 4.41631e-07 loss) | |
| I0407 16:34:09.893039 1004 solver.cpp:245] Train net output #41: loss/loss20 = 8.70252e-06 (* 0.0454545 = 3.95569e-07 loss) | |
| I0407 16:34:09.893054 1004 solver.cpp:245] Train net output #42: loss/loss21 = 9.48488e-06 (* 0.0454545 = 4.31131e-07 loss) | |
| I0407 16:34:09.893066 1004 solver.cpp:245] Train net output #43: loss/loss22 = 9.42528e-06 (* 0.0454545 = 4.28422e-07 loss) | |
| I0407 16:34:09.893079 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:34:09.893090 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000325228 | |
| I0407 16:34:09.893103 1004 sgd_solver.cpp:106] Iteration 60500, lr = 0.000879 | |
| I0407 16:34:48.769438 1004 solver.cpp:229] Iteration 61000, loss = 0.996925 | |
| I0407 16:34:48.769616 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:34:48.769634 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:34:48.769647 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.1875 | |
| I0407 16:34:48.769659 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 16:34:48.769671 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0 | |
| I0407 16:34:48.769683 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.25 | |
| I0407 16:34:48.769695 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.5625 | |
| I0407 16:34:48.769706 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.75 | |
| I0407 16:34:48.769718 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.875 | |
| I0407 16:34:48.769729 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.875 | |
| I0407 16:34:48.769742 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:34:48.769754 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:34:48.769767 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:34:48.769778 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:34:48.769788 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:34:48.769800 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:34:48.769811 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:34:48.769822 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:34:48.769834 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:34:48.769845 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:34:48.769856 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:34:48.769868 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:34:48.769883 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.48478 (* 0.0454545 = 0.158399 loss) | |
| I0407 16:34:48.769898 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.53058 (* 0.0454545 = 0.160481 loss) | |
| I0407 16:34:48.769912 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.6465 (* 0.0454545 = 0.16575 loss) | |
| I0407 16:34:48.769927 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.65901 (* 0.0454545 = 0.166319 loss) | |
| I0407 16:34:48.769940 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.80315 (* 0.0454545 = 0.17287 loss) | |
| I0407 16:34:48.769954 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.90459 (* 0.0454545 = 0.132027 loss) | |
| I0407 16:34:48.769968 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.9837 (* 0.0454545 = 0.0901682 loss) | |
| I0407 16:34:48.769981 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.12579 (* 0.0454545 = 0.0511721 loss) | |
| I0407 16:34:48.769995 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.586753 (* 0.0454545 = 0.0266706 loss) | |
| I0407 16:34:48.770009 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.655328 (* 0.0454545 = 0.0297876 loss) | |
| I0407 16:34:48.770025 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000372098 (* 0.0454545 = 1.69135e-05 loss) | |
| I0407 16:34:48.770038 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000324214 (* 0.0454545 = 1.4737e-05 loss) | |
| I0407 16:34:48.770052 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000330838 (* 0.0454545 = 1.50381e-05 loss) | |
| I0407 16:34:48.770066 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000382135 (* 0.0454545 = 1.73698e-05 loss) | |
| I0407 16:34:48.770084 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000387548 (* 0.0454545 = 1.76158e-05 loss) | |
| I0407 16:34:48.770098 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000321242 (* 0.0454545 = 1.46019e-05 loss) | |
| I0407 16:34:48.770112 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000397156 (* 0.0454545 = 1.80526e-05 loss) | |
| I0407 16:34:48.770143 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000433159 (* 0.0454545 = 1.96891e-05 loss) | |
| I0407 16:34:48.770159 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000350355 (* 0.0454545 = 1.59252e-05 loss) | |
| I0407 16:34:48.770172 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000367892 (* 0.0454545 = 1.67224e-05 loss) | |
| I0407 16:34:48.770186 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000399928 (* 0.0454545 = 1.81785e-05 loss) | |
| I0407 16:34:48.770200 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000336906 (* 0.0454545 = 1.53139e-05 loss) | |
| I0407 16:34:48.770212 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:34:48.770225 1004 solver.cpp:245] Train net output #45: total_confidence = 4.652e-06 | |
| I0407 16:34:48.770237 1004 sgd_solver.cpp:106] Iteration 61000, lr = 0.000878 | |
| I0407 16:35:28.323962 1004 solver.cpp:229] Iteration 61500, loss = 0.995097 | |
| I0407 16:35:28.324105 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:35:28.324123 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.125 | |
| I0407 16:35:28.324136 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:35:28.324148 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.25 | |
| I0407 16:35:28.324161 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.375 | |
| I0407 16:35:28.324173 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5 | |
| I0407 16:35:28.324184 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.625 | |
| I0407 16:35:28.324196 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:35:28.324208 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:35:28.324220 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:35:28.324232 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:35:28.324244 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:35:28.324254 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:35:28.324266 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:35:28.324277 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:35:28.324290 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:35:28.324301 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:35:28.324312 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:35:28.324324 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:35:28.324336 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:35:28.324347 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:35:28.324358 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:35:28.324374 1004 solver.cpp:245] Train net output #22: loss/loss01 = 2.79414 (* 0.0454545 = 0.127006 loss) | |
| I0407 16:35:28.324389 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.07552 (* 0.0454545 = 0.139797 loss) | |
| I0407 16:35:28.324404 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.18692 (* 0.0454545 = 0.14486 loss) | |
| I0407 16:35:28.324417 1004 solver.cpp:245] Train net output #25: loss/loss04 = 2.83853 (* 0.0454545 = 0.129024 loss) | |
| I0407 16:35:28.324431 1004 solver.cpp:245] Train net output #26: loss/loss05 = 2.23412 (* 0.0454545 = 0.101551 loss) | |
| I0407 16:35:28.324445 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.09643 (* 0.0454545 = 0.0952922 loss) | |
| I0407 16:35:28.324458 1004 solver.cpp:245] Train net output #28: loss/loss07 = 2.23158 (* 0.0454545 = 0.101435 loss) | |
| I0407 16:35:28.324472 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.579228 (* 0.0454545 = 0.0263286 loss) | |
| I0407 16:35:28.324487 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.00332556 (* 0.0454545 = 0.000151162 loss) | |
| I0407 16:35:28.324501 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.00099284 (* 0.0454545 = 4.51291e-05 loss) | |
| I0407 16:35:28.324517 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000126668 (* 0.0454545 = 5.75763e-06 loss) | |
| I0407 16:35:28.324530 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000101547 (* 0.0454545 = 4.61577e-06 loss) | |
| I0407 16:35:28.324544 1004 solver.cpp:245] Train net output #34: loss/loss13 = 9.42457e-05 (* 0.0454545 = 4.28389e-06 loss) | |
| I0407 16:35:28.324558 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000117348 (* 0.0454545 = 5.33399e-06 loss) | |
| I0407 16:35:28.324573 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000117696 (* 0.0454545 = 5.34982e-06 loss) | |
| I0407 16:35:28.324586 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000100885 (* 0.0454545 = 4.58567e-06 loss) | |
| I0407 16:35:28.324600 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000114743 (* 0.0454545 = 5.21558e-06 loss) | |
| I0407 16:35:28.324627 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000124562 (* 0.0454545 = 5.66193e-06 loss) | |
| I0407 16:35:28.324642 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000114494 (* 0.0454545 = 5.20426e-06 loss) | |
| I0407 16:35:28.324656 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000116052 (* 0.0454545 = 5.27509e-06 loss) | |
| I0407 16:35:28.324671 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000129144 (* 0.0454545 = 5.87018e-06 loss) | |
| I0407 16:35:28.324684 1004 solver.cpp:245] Train net output #43: loss/loss22 = 9.51048e-05 (* 0.0454545 = 4.32295e-06 loss) | |
| I0407 16:35:28.324697 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:35:28.324708 1004 solver.cpp:245] Train net output #45: total_confidence = 0.00402658 | |
| I0407 16:35:28.324720 1004 sgd_solver.cpp:106] Iteration 61500, lr = 0.000877 | |
| I0407 16:36:07.076725 1004 solver.cpp:229] Iteration 62000, loss = 0.992541 | |
| I0407 16:36:07.076823 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:36:07.076843 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:36:07.076855 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:36:07.076867 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 16:36:07.076879 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 16:36:07.076894 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 16:36:07.076907 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 16:36:07.076920 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:36:07.076931 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:36:07.076943 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:36:07.076959 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:36:07.076984 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:36:07.077008 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:36:07.077021 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:36:07.077033 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:36:07.077044 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:36:07.077056 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:36:07.077067 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:36:07.077081 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:36:07.077093 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:36:07.077105 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:36:07.077117 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:36:07.077132 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.22791 (* 0.0454545 = 0.146723 loss) | |
| I0407 16:36:07.077147 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.75279 (* 0.0454545 = 0.170581 loss) | |
| I0407 16:36:07.077162 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.54381 (* 0.0454545 = 0.161082 loss) | |
| I0407 16:36:07.077175 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.81809 (* 0.0454545 = 0.173549 loss) | |
| I0407 16:36:07.077188 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.36562 (* 0.0454545 = 0.152983 loss) | |
| I0407 16:36:07.077203 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.7791 (* 0.0454545 = 0.126323 loss) | |
| I0407 16:36:07.077215 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.26572 (* 0.0454545 = 0.0575327 loss) | |
| I0407 16:36:07.077229 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.567677 (* 0.0454545 = 0.0258035 loss) | |
| I0407 16:36:07.077242 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.63351 (* 0.0454545 = 0.0287959 loss) | |
| I0407 16:36:07.077256 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0222286 (* 0.0454545 = 0.00101039 loss) | |
| I0407 16:36:07.077271 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.00112343 (* 0.0454545 = 5.10648e-05 loss) | |
| I0407 16:36:07.077286 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00101717 (* 0.0454545 = 4.62352e-05 loss) | |
| I0407 16:36:07.077299 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.00107942 (* 0.0454545 = 4.90644e-05 loss) | |
| I0407 16:36:07.077314 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00115559 (* 0.0454545 = 5.25269e-05 loss) | |
| I0407 16:36:07.077328 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.00125085 (* 0.0454545 = 5.68569e-05 loss) | |
| I0407 16:36:07.077342 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000972491 (* 0.0454545 = 4.42041e-05 loss) | |
| I0407 16:36:07.077358 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.00120938 (* 0.0454545 = 5.49718e-05 loss) | |
| I0407 16:36:07.077389 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.00130492 (* 0.0454545 = 5.93145e-05 loss) | |
| I0407 16:36:07.077404 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00112034 (* 0.0454545 = 5.09244e-05 loss) | |
| I0407 16:36:07.077419 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.00116856 (* 0.0454545 = 5.31162e-05 loss) | |
| I0407 16:36:07.077432 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00125595 (* 0.0454545 = 5.70886e-05 loss) | |
| I0407 16:36:07.077446 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00106403 (* 0.0454545 = 4.8365e-05 loss) | |
| I0407 16:36:07.077458 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:36:07.077469 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000721559 | |
| I0407 16:36:07.077483 1004 sgd_solver.cpp:106] Iteration 62000, lr = 0.000876 | |
| I0407 16:36:45.943537 1004 solver.cpp:229] Iteration 62500, loss = 0.990481 | |
| I0407 16:36:45.943673 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:36:45.943694 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:36:45.943707 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:36:45.943719 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 16:36:45.943732 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 16:36:45.943743 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5 | |
| I0407 16:36:45.943756 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.625 | |
| I0407 16:36:45.943768 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 16:36:45.943780 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:36:45.943791 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:36:45.943804 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:36:45.943814 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:36:45.943826 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:36:45.943837 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:36:45.943850 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:36:45.943861 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:36:45.943871 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:36:45.943882 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:36:45.943894 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:36:45.943907 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:36:45.943917 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:36:45.943929 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:36:45.943944 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.52941 (* 0.0454545 = 0.160428 loss) | |
| I0407 16:36:45.943959 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.83765 (* 0.0454545 = 0.174439 loss) | |
| I0407 16:36:45.943974 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.74235 (* 0.0454545 = 0.170107 loss) | |
| I0407 16:36:45.943987 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.33059 (* 0.0454545 = 0.15139 loss) | |
| I0407 16:36:45.944001 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.15208 (* 0.0454545 = 0.143277 loss) | |
| I0407 16:36:45.944015 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.18555 (* 0.0454545 = 0.0993432 loss) | |
| I0407 16:36:45.944028 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.74957 (* 0.0454545 = 0.0795257 loss) | |
| I0407 16:36:45.944042 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.653858 (* 0.0454545 = 0.0297208 loss) | |
| I0407 16:36:45.944056 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0239153 (* 0.0454545 = 0.00108706 loss) | |
| I0407 16:36:45.944070 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.00864262 (* 0.0454545 = 0.000392846 loss) | |
| I0407 16:36:45.944089 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.00021827 (* 0.0454545 = 9.92135e-06 loss) | |
| I0407 16:36:45.944103 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000189807 (* 0.0454545 = 8.62761e-06 loss) | |
| I0407 16:36:45.944118 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000199754 (* 0.0454545 = 9.07972e-06 loss) | |
| I0407 16:36:45.944133 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000219858 (* 0.0454545 = 9.99354e-06 loss) | |
| I0407 16:36:45.944146 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000222077 (* 0.0454545 = 1.00944e-05 loss) | |
| I0407 16:36:45.944160 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000176245 (* 0.0454545 = 8.01114e-06 loss) | |
| I0407 16:36:45.944175 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000232343 (* 0.0454545 = 1.05611e-05 loss) | |
| I0407 16:36:45.944375 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000246156 (* 0.0454545 = 1.11889e-05 loss) | |
| I0407 16:36:45.944392 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000190234 (* 0.0454545 = 8.64699e-06 loss) | |
| I0407 16:36:45.944406 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000212545 (* 0.0454545 = 9.66112e-06 loss) | |
| I0407 16:36:45.944421 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000228788 (* 0.0454545 = 1.03994e-05 loss) | |
| I0407 16:36:45.944434 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000199786 (* 0.0454545 = 9.08117e-06 loss) | |
| I0407 16:36:45.944447 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:36:45.944458 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000265377 | |
| I0407 16:36:45.944471 1004 sgd_solver.cpp:106] Iteration 62500, lr = 0.000875 | |
| I0407 16:37:25.038573 1004 solver.cpp:229] Iteration 63000, loss = 0.993061 | |
| I0407 16:37:25.038692 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:37:25.038712 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:37:25.038725 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:37:25.038738 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 16:37:25.038749 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.3125 | |
| I0407 16:37:25.038761 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 16:37:25.038774 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 16:37:25.038785 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:37:25.038799 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:37:25.038810 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 16:37:25.038822 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:37:25.038833 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:37:25.038846 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:37:25.038856 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:37:25.038867 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:37:25.038879 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:37:25.038890 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:37:25.038902 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:37:25.038913 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:37:25.038928 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:37:25.038939 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:37:25.038951 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:37:25.038967 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.30398 (* 0.0454545 = 0.150181 loss) | |
| I0407 16:37:25.038981 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.59564 (* 0.0454545 = 0.163438 loss) | |
| I0407 16:37:25.038995 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.75306 (* 0.0454545 = 0.170594 loss) | |
| I0407 16:37:25.039008 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.6701 (* 0.0454545 = 0.166823 loss) | |
| I0407 16:37:25.039022 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.31035 (* 0.0454545 = 0.15047 loss) | |
| I0407 16:37:25.039036 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.73095 (* 0.0454545 = 0.124134 loss) | |
| I0407 16:37:25.039050 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.47453 (* 0.0454545 = 0.0670239 loss) | |
| I0407 16:37:25.039064 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.5296 (* 0.0454545 = 0.0240727 loss) | |
| I0407 16:37:25.039078 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.526575 (* 0.0454545 = 0.0239352 loss) | |
| I0407 16:37:25.039091 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.665202 (* 0.0454545 = 0.0302364 loss) | |
| I0407 16:37:25.039106 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000312196 (* 0.0454545 = 1.41907e-05 loss) | |
| I0407 16:37:25.039120 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000290891 (* 0.0454545 = 1.32223e-05 loss) | |
| I0407 16:37:25.039134 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000258848 (* 0.0454545 = 1.17658e-05 loss) | |
| I0407 16:37:25.039149 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000251342 (* 0.0454545 = 1.14246e-05 loss) | |
| I0407 16:37:25.039162 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000275715 (* 0.0454545 = 1.25325e-05 loss) | |
| I0407 16:37:25.039175 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000259704 (* 0.0454545 = 1.18047e-05 loss) | |
| I0407 16:37:25.039189 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000244798 (* 0.0454545 = 1.11272e-05 loss) | |
| I0407 16:37:25.039219 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000311246 (* 0.0454545 = 1.41475e-05 loss) | |
| I0407 16:37:25.039235 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000267268 (* 0.0454545 = 1.21485e-05 loss) | |
| I0407 16:37:25.039249 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000253387 (* 0.0454545 = 1.15176e-05 loss) | |
| I0407 16:37:25.039263 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00028109 (* 0.0454545 = 1.27768e-05 loss) | |
| I0407 16:37:25.039278 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000267065 (* 0.0454545 = 1.21393e-05 loss) | |
| I0407 16:37:25.039289 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:37:25.039300 1004 solver.cpp:245] Train net output #45: total_confidence = 9.58047e-05 | |
| I0407 16:37:25.039314 1004 sgd_solver.cpp:106] Iteration 63000, lr = 0.000874 | |
| I0407 16:38:04.200525 1004 solver.cpp:229] Iteration 63500, loss = 0.987642 | |
| I0407 16:38:04.200657 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.25 | |
| I0407 16:38:04.200676 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:38:04.200690 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:38:04.200702 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 16:38:04.200714 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 16:38:04.200726 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 16:38:04.200738 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.625 | |
| I0407 16:38:04.200750 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 16:38:04.200762 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:38:04.200774 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:38:04.200785 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:38:04.200798 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:38:04.200809 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:38:04.200820 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:38:04.200831 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:38:04.200844 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:38:04.200855 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:38:04.200866 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:38:04.200877 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:38:04.200889 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:38:04.200901 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:38:04.200912 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:38:04.200930 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.28861 (* 0.0454545 = 0.149482 loss) | |
| I0407 16:38:04.200945 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.59278 (* 0.0454545 = 0.163308 loss) | |
| I0407 16:38:04.200959 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.47027 (* 0.0454545 = 0.15774 loss) | |
| I0407 16:38:04.200973 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.64966 (* 0.0454545 = 0.165894 loss) | |
| I0407 16:38:04.200987 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.25587 (* 0.0454545 = 0.147994 loss) | |
| I0407 16:38:04.201000 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.8902 (* 0.0454545 = 0.131373 loss) | |
| I0407 16:38:04.201014 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.74185 (* 0.0454545 = 0.0791748 loss) | |
| I0407 16:38:04.201027 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.856815 (* 0.0454545 = 0.0389461 loss) | |
| I0407 16:38:04.201041 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.324719 (* 0.0454545 = 0.01476 loss) | |
| I0407 16:38:04.201056 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0258411 (* 0.0454545 = 0.00117459 loss) | |
| I0407 16:38:04.201069 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000194605 (* 0.0454545 = 8.84569e-06 loss) | |
| I0407 16:38:04.201083 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000178978 (* 0.0454545 = 8.13535e-06 loss) | |
| I0407 16:38:04.201097 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000173212 (* 0.0454545 = 7.87327e-06 loss) | |
| I0407 16:38:04.201112 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000206663 (* 0.0454545 = 9.39376e-06 loss) | |
| I0407 16:38:04.201125 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000188313 (* 0.0454545 = 8.55969e-06 loss) | |
| I0407 16:38:04.201139 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000175245 (* 0.0454545 = 7.96569e-06 loss) | |
| I0407 16:38:04.201153 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000196648 (* 0.0454545 = 8.93853e-06 loss) | |
| I0407 16:38:04.201180 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.00020598 (* 0.0454545 = 9.36274e-06 loss) | |
| I0407 16:38:04.201195 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000171992 (* 0.0454545 = 7.81782e-06 loss) | |
| I0407 16:38:04.201210 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000192203 (* 0.0454545 = 8.7365e-06 loss) | |
| I0407 16:38:04.201223 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000211196 (* 0.0454545 = 9.59981e-06 loss) | |
| I0407 16:38:04.201237 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000189225 (* 0.0454545 = 8.60116e-06 loss) | |
| I0407 16:38:04.201249 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:38:04.201261 1004 solver.cpp:245] Train net output #45: total_confidence = 3.7169e-05 | |
| I0407 16:38:04.201273 1004 sgd_solver.cpp:106] Iteration 63500, lr = 0.000873 | |
| I0407 16:38:43.083632 1004 solver.cpp:229] Iteration 64000, loss = 0.990287 | |
| I0407 16:38:43.083760 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.1875 | |
| I0407 16:38:43.083778 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:38:43.083791 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 16:38:43.083803 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.25 | |
| I0407 16:38:43.083816 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 16:38:43.083827 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 16:38:43.083839 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 16:38:43.083852 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:38:43.083863 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:38:43.083874 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 16:38:43.083886 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:38:43.083897 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:38:43.083909 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:38:43.083925 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:38:43.083936 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:38:43.083948 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:38:43.083961 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:38:43.083971 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:38:43.083983 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:38:43.083994 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:38:43.084007 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:38:43.084017 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:38:43.084033 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.16403 (* 0.0454545 = 0.143819 loss) | |
| I0407 16:38:43.084048 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.38872 (* 0.0454545 = 0.154033 loss) | |
| I0407 16:38:43.084063 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.4103 (* 0.0454545 = 0.155014 loss) | |
| I0407 16:38:43.084076 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.02786 (* 0.0454545 = 0.13763 loss) | |
| I0407 16:38:43.084089 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.00278 (* 0.0454545 = 0.13649 loss) | |
| I0407 16:38:43.084103 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.487 (* 0.0454545 = 0.113046 loss) | |
| I0407 16:38:43.084117 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.10313 (* 0.0454545 = 0.0501423 loss) | |
| I0407 16:38:43.084131 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.348012 (* 0.0454545 = 0.0158187 loss) | |
| I0407 16:38:43.084146 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.415504 (* 0.0454545 = 0.0188865 loss) | |
| I0407 16:38:43.084158 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.43266 (* 0.0454545 = 0.0196663 loss) | |
| I0407 16:38:43.084173 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000596053 (* 0.0454545 = 2.70933e-05 loss) | |
| I0407 16:38:43.084187 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00045367 (* 0.0454545 = 2.06213e-05 loss) | |
| I0407 16:38:43.084202 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000486237 (* 0.0454545 = 2.21017e-05 loss) | |
| I0407 16:38:43.084215 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000530432 (* 0.0454545 = 2.41105e-05 loss) | |
| I0407 16:38:43.084229 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000558386 (* 0.0454545 = 2.53812e-05 loss) | |
| I0407 16:38:43.084244 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.00050347 (* 0.0454545 = 2.2885e-05 loss) | |
| I0407 16:38:43.084257 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000593373 (* 0.0454545 = 2.69715e-05 loss) | |
| I0407 16:38:43.084288 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000623389 (* 0.0454545 = 2.83359e-05 loss) | |
| I0407 16:38:43.084305 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000529547 (* 0.0454545 = 2.40703e-05 loss) | |
| I0407 16:38:43.084317 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000496493 (* 0.0454545 = 2.25679e-05 loss) | |
| I0407 16:38:43.084332 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000650614 (* 0.0454545 = 2.95734e-05 loss) | |
| I0407 16:38:43.084347 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000554918 (* 0.0454545 = 2.52235e-05 loss) | |
| I0407 16:38:43.084358 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:38:43.084370 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000751509 | |
| I0407 16:38:43.084383 1004 sgd_solver.cpp:106] Iteration 64000, lr = 0.000872 | |
| I0407 16:39:22.119001 1004 solver.cpp:229] Iteration 64500, loss = 0.992696 | |
| I0407 16:39:22.119113 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.25 | |
| I0407 16:39:22.119132 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:39:22.119145 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:39:22.119158 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.25 | |
| I0407 16:39:22.119170 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.4375 | |
| I0407 16:39:22.119182 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.625 | |
| I0407 16:39:22.119194 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 16:39:22.119206 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:39:22.119218 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:39:22.119230 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:39:22.119241 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:39:22.119253 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:39:22.119264 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:39:22.119277 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:39:22.119288 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:39:22.119299 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:39:22.119312 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:39:22.119336 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:39:22.119349 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:39:22.119361 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:39:22.119372 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:39:22.119385 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:39:22.119400 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.10318 (* 0.0454545 = 0.141054 loss) | |
| I0407 16:39:22.119415 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.3887 (* 0.0454545 = 0.154032 loss) | |
| I0407 16:39:22.119428 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.47451 (* 0.0454545 = 0.157932 loss) | |
| I0407 16:39:22.119442 1004 solver.cpp:245] Train net output #25: loss/loss04 = 2.98322 (* 0.0454545 = 0.135601 loss) | |
| I0407 16:39:22.119457 1004 solver.cpp:245] Train net output #26: loss/loss05 = 2.58208 (* 0.0454545 = 0.117367 loss) | |
| I0407 16:39:22.119470 1004 solver.cpp:245] Train net output #27: loss/loss06 = 1.96878 (* 0.0454545 = 0.0894899 loss) | |
| I0407 16:39:22.119483 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.947268 (* 0.0454545 = 0.0430577 loss) | |
| I0407 16:39:22.119498 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.372978 (* 0.0454545 = 0.0169535 loss) | |
| I0407 16:39:22.119511 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0588741 (* 0.0454545 = 0.0026761 loss) | |
| I0407 16:39:22.119526 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0232771 (* 0.0454545 = 0.00105805 loss) | |
| I0407 16:39:22.119540 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.00059408 (* 0.0454545 = 2.70036e-05 loss) | |
| I0407 16:39:22.119554 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000619611 (* 0.0454545 = 2.81641e-05 loss) | |
| I0407 16:39:22.119568 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000666927 (* 0.0454545 = 3.03149e-05 loss) | |
| I0407 16:39:22.119582 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000694172 (* 0.0454545 = 3.15533e-05 loss) | |
| I0407 16:39:22.119596 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000736927 (* 0.0454545 = 3.34967e-05 loss) | |
| I0407 16:39:22.119609 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000596566 (* 0.0454545 = 2.71166e-05 loss) | |
| I0407 16:39:22.119623 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000703356 (* 0.0454545 = 3.19707e-05 loss) | |
| I0407 16:39:22.119655 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000735377 (* 0.0454545 = 3.34262e-05 loss) | |
| I0407 16:39:22.119670 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000570103 (* 0.0454545 = 2.59138e-05 loss) | |
| I0407 16:39:22.119684 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000680145 (* 0.0454545 = 3.09157e-05 loss) | |
| I0407 16:39:22.119699 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000697389 (* 0.0454545 = 3.16995e-05 loss) | |
| I0407 16:39:22.119712 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000693744 (* 0.0454545 = 3.15338e-05 loss) | |
| I0407 16:39:22.119724 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:39:22.119736 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000389114 | |
| I0407 16:39:22.119750 1004 sgd_solver.cpp:106] Iteration 64500, lr = 0.000871 | |
| I0407 16:40:01.449442 1004 solver.cpp:338] Iteration 65000, Testing net (#0) | |
| I0407 16:40:09.404753 1004 solver.cpp:393] Test loss: 0.89467 | |
| I0407 16:40:09.404803 1004 solver.cpp:406] Test net output #0: loss/accuracy01 = 0.36 | |
| I0407 16:40:09.404819 1004 solver.cpp:406] Test net output #1: loss/accuracy02 = 0.107 | |
| I0407 16:40:09.404831 1004 solver.cpp:406] Test net output #2: loss/accuracy03 = 0.076 | |
| I0407 16:40:09.404844 1004 solver.cpp:406] Test net output #3: loss/accuracy04 = 0.08 | |
| I0407 16:40:09.404855 1004 solver.cpp:406] Test net output #4: loss/accuracy05 = 0.205 | |
| I0407 16:40:09.404866 1004 solver.cpp:406] Test net output #5: loss/accuracy06 = 0.496 | |
| I0407 16:40:09.404878 1004 solver.cpp:406] Test net output #6: loss/accuracy07 = 0.894 | |
| I0407 16:40:09.404891 1004 solver.cpp:406] Test net output #7: loss/accuracy08 = 0.97 | |
| I0407 16:40:09.404901 1004 solver.cpp:406] Test net output #8: loss/accuracy09 = 0.995 | |
| I0407 16:40:09.404912 1004 solver.cpp:406] Test net output #9: loss/accuracy10 = 0.998 | |
| I0407 16:40:09.404927 1004 solver.cpp:406] Test net output #10: loss/accuracy11 = 1 | |
| I0407 16:40:09.404938 1004 solver.cpp:406] Test net output #11: loss/accuracy12 = 1 | |
| I0407 16:40:09.404949 1004 solver.cpp:406] Test net output #12: loss/accuracy13 = 1 | |
| I0407 16:40:09.404960 1004 solver.cpp:406] Test net output #13: loss/accuracy14 = 1 | |
| I0407 16:40:09.404973 1004 solver.cpp:406] Test net output #14: loss/accuracy15 = 1 | |
| I0407 16:40:09.404983 1004 solver.cpp:406] Test net output #15: loss/accuracy16 = 1 | |
| I0407 16:40:09.404994 1004 solver.cpp:406] Test net output #16: loss/accuracy17 = 1 | |
| I0407 16:40:09.405004 1004 solver.cpp:406] Test net output #17: loss/accuracy18 = 1 | |
| I0407 16:40:09.405015 1004 solver.cpp:406] Test net output #18: loss/accuracy19 = 1 | |
| I0407 16:40:09.405026 1004 solver.cpp:406] Test net output #19: loss/accuracy20 = 1 | |
| I0407 16:40:09.405037 1004 solver.cpp:406] Test net output #20: loss/accuracy21 = 1 | |
| I0407 16:40:09.405048 1004 solver.cpp:406] Test net output #21: loss/accuracy22 = 1 | |
| I0407 16:40:09.405064 1004 solver.cpp:406] Test net output #22: loss/loss01 = 3.00187 (* 0.0454545 = 0.136449 loss) | |
| I0407 16:40:09.405078 1004 solver.cpp:406] Test net output #23: loss/loss02 = 3.26805 (* 0.0454545 = 0.148548 loss) | |
| I0407 16:40:09.405092 1004 solver.cpp:406] Test net output #24: loss/loss03 = 3.38182 (* 0.0454545 = 0.153719 loss) | |
| I0407 16:40:09.405107 1004 solver.cpp:406] Test net output #25: loss/loss04 = 3.32236 (* 0.0454545 = 0.151017 loss) | |
| I0407 16:40:09.405120 1004 solver.cpp:406] Test net output #26: loss/loss05 = 3.25097 (* 0.0454545 = 0.147772 loss) | |
| I0407 16:40:09.405134 1004 solver.cpp:406] Test net output #27: loss/loss06 = 2.29869 (* 0.0454545 = 0.104486 loss) | |
| I0407 16:40:09.405148 1004 solver.cpp:406] Test net output #28: loss/loss07 = 0.76149 (* 0.0454545 = 0.0346132 loss) | |
| I0407 16:40:09.405160 1004 solver.cpp:406] Test net output #29: loss/loss08 = 0.283204 (* 0.0454545 = 0.0128729 loss) | |
| I0407 16:40:09.405174 1004 solver.cpp:406] Test net output #30: loss/loss09 = 0.0671729 (* 0.0454545 = 0.00305331 loss) | |
| I0407 16:40:09.405189 1004 solver.cpp:406] Test net output #31: loss/loss10 = 0.0352257 (* 0.0454545 = 0.00160117 loss) | |
| I0407 16:40:09.405202 1004 solver.cpp:406] Test net output #32: loss/loss11 = 0.0010431 (* 0.0454545 = 4.74137e-05 loss) | |
| I0407 16:40:09.405216 1004 solver.cpp:406] Test net output #33: loss/loss12 = 0.000939298 (* 0.0454545 = 4.26954e-05 loss) | |
| I0407 16:40:09.405231 1004 solver.cpp:406] Test net output #34: loss/loss13 = 0.000938294 (* 0.0454545 = 4.26497e-05 loss) | |
| I0407 16:40:09.405246 1004 solver.cpp:406] Test net output #35: loss/loss14 = 0.000990492 (* 0.0454545 = 4.50224e-05 loss) | |
| I0407 16:40:09.405259 1004 solver.cpp:406] Test net output #36: loss/loss15 = 0.000979141 (* 0.0454545 = 4.45064e-05 loss) | |
| I0407 16:40:09.405273 1004 solver.cpp:406] Test net output #37: loss/loss16 = 0.000970843 (* 0.0454545 = 4.41292e-05 loss) | |
| I0407 16:40:09.405287 1004 solver.cpp:406] Test net output #38: loss/loss17 = 0.00101964 (* 0.0454545 = 4.63471e-05 loss) | |
| I0407 16:40:09.405334 1004 solver.cpp:406] Test net output #39: loss/loss18 = 0.00111328 (* 0.0454545 = 5.06035e-05 loss) | |
| I0407 16:40:09.405349 1004 solver.cpp:406] Test net output #40: loss/loss19 = 0.000928525 (* 0.0454545 = 4.22057e-05 loss) | |
| I0407 16:40:09.405364 1004 solver.cpp:406] Test net output #41: loss/loss20 = 0.000948419 (* 0.0454545 = 4.311e-05 loss) | |
| I0407 16:40:09.405377 1004 solver.cpp:406] Test net output #42: loss/loss21 = 0.00101446 (* 0.0454545 = 4.61117e-05 loss) | |
| I0407 16:40:09.405390 1004 solver.cpp:406] Test net output #43: loss/loss22 = 0.000999628 (* 0.0454545 = 4.54376e-05 loss) | |
| I0407 16:40:09.405402 1004 solver.cpp:406] Test net output #44: total_accuracy = 0.001 | |
| I0407 16:40:09.405413 1004 solver.cpp:406] Test net output #45: total_confidence = 0.000128334 | |
| I0407 16:40:09.427716 1004 solver.cpp:229] Iteration 65000, loss = 0.983656 | |
| I0407 16:40:09.427750 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.25 | |
| I0407 16:40:09.427768 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:40:09.427780 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.1875 | |
| I0407 16:40:09.427793 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 16:40:09.427804 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.5 | |
| I0407 16:40:09.427816 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5625 | |
| I0407 16:40:09.427827 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 16:40:09.427839 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 16:40:09.427850 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:40:09.427865 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:40:09.427877 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:40:09.427888 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:40:09.427901 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:40:09.427911 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:40:09.427923 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:40:09.427934 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:40:09.427945 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:40:09.427958 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:40:09.427968 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:40:09.427980 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:40:09.427991 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:40:09.428004 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:40:09.428017 1004 solver.cpp:245] Train net output #22: loss/loss01 = 2.45513 (* 0.0454545 = 0.111597 loss) | |
| I0407 16:40:09.428032 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.14356 (* 0.0454545 = 0.142889 loss) | |
| I0407 16:40:09.428045 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.13051 (* 0.0454545 = 0.142296 loss) | |
| I0407 16:40:09.428059 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.00581 (* 0.0454545 = 0.136628 loss) | |
| I0407 16:40:09.428076 1004 solver.cpp:245] Train net output #26: loss/loss05 = 2.20178 (* 0.0454545 = 0.100081 loss) | |
| I0407 16:40:09.428089 1004 solver.cpp:245] Train net output #27: loss/loss06 = 1.75733 (* 0.0454545 = 0.0798786 loss) | |
| I0407 16:40:09.428103 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.00491 (* 0.0454545 = 0.0456778 loss) | |
| I0407 16:40:09.428117 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.0488049 (* 0.0454545 = 0.00221841 loss) | |
| I0407 16:40:09.428133 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0103625 (* 0.0454545 = 0.000471021 loss) | |
| I0407 16:40:09.428145 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.00266077 (* 0.0454545 = 0.000120944 loss) | |
| I0407 16:40:09.428176 1004 solver.cpp:245] Train net output #32: loss/loss11 = 4.93241e-06 (* 0.0454545 = 2.242e-07 loss) | |
| I0407 16:40:09.428192 1004 solver.cpp:245] Train net output #33: loss/loss12 = 4.99947e-06 (* 0.0454545 = 2.27249e-07 loss) | |
| I0407 16:40:09.428207 1004 solver.cpp:245] Train net output #34: loss/loss13 = 5.16341e-06 (* 0.0454545 = 2.347e-07 loss) | |
| I0407 16:40:09.428221 1004 solver.cpp:245] Train net output #35: loss/loss14 = 4.44065e-06 (* 0.0454545 = 2.01848e-07 loss) | |
| I0407 16:40:09.428236 1004 solver.cpp:245] Train net output #36: loss/loss15 = 4.8281e-06 (* 0.0454545 = 2.19459e-07 loss) | |
| I0407 16:40:09.428249 1004 solver.cpp:245] Train net output #37: loss/loss16 = 4.53007e-06 (* 0.0454545 = 2.05912e-07 loss) | |
| I0407 16:40:09.428263 1004 solver.cpp:245] Train net output #38: loss/loss17 = 4.29163e-06 (* 0.0454545 = 1.95074e-07 loss) | |
| I0407 16:40:09.428277 1004 solver.cpp:245] Train net output #39: loss/loss18 = 5.29006e-06 (* 0.0454545 = 2.40457e-07 loss) | |
| I0407 16:40:09.428292 1004 solver.cpp:245] Train net output #40: loss/loss19 = 4.52262e-06 (* 0.0454545 = 2.05573e-07 loss) | |
| I0407 16:40:09.428305 1004 solver.cpp:245] Train net output #41: loss/loss20 = 4.30654e-06 (* 0.0454545 = 1.95752e-07 loss) | |
| I0407 16:40:09.428319 1004 solver.cpp:245] Train net output #42: loss/loss21 = 5.23791e-06 (* 0.0454545 = 2.38087e-07 loss) | |
| I0407 16:40:09.428333 1004 solver.cpp:245] Train net output #43: loss/loss22 = 5.1485e-06 (* 0.0454545 = 2.34023e-07 loss) | |
| I0407 16:40:09.428344 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:40:09.428356 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000336043 | |
| I0407 16:40:09.428371 1004 sgd_solver.cpp:106] Iteration 65000, lr = 0.00087 | |
| I0407 16:40:48.843886 1004 solver.cpp:229] Iteration 65500, loss = 0.996828 | |
| I0407 16:40:48.844051 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.1875 | |
| I0407 16:40:48.844080 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.125 | |
| I0407 16:40:48.844094 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:40:48.844107 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 16:40:48.844120 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 16:40:48.844132 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 16:40:48.844144 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.625 | |
| I0407 16:40:48.844156 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 16:40:48.844169 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.875 | |
| I0407 16:40:48.844180 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 16:40:48.844192 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:40:48.844204 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:40:48.844216 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:40:48.844228 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:40:48.844239 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:40:48.844250 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:40:48.844262 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:40:48.844274 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:40:48.844285 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:40:48.844296 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:40:48.844307 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:40:48.844319 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:40:48.844334 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.14024 (* 0.0454545 = 0.142738 loss) | |
| I0407 16:40:48.844348 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.51547 (* 0.0454545 = 0.159794 loss) | |
| I0407 16:40:48.844362 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.5729 (* 0.0454545 = 0.162405 loss) | |
| I0407 16:40:48.844377 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.60581 (* 0.0454545 = 0.1639 loss) | |
| I0407 16:40:48.844390 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.48895 (* 0.0454545 = 0.158589 loss) | |
| I0407 16:40:48.844404 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.73808 (* 0.0454545 = 0.124458 loss) | |
| I0407 16:40:48.844418 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.63578 (* 0.0454545 = 0.0743534 loss) | |
| I0407 16:40:48.844431 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.957273 (* 0.0454545 = 0.0435124 loss) | |
| I0407 16:40:48.844445 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.831411 (* 0.0454545 = 0.0377914 loss) | |
| I0407 16:40:48.844458 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.469352 (* 0.0454545 = 0.0213342 loss) | |
| I0407 16:40:48.844473 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.00019238 (* 0.0454545 = 8.74455e-06 loss) | |
| I0407 16:40:48.844487 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000160171 (* 0.0454545 = 7.28052e-06 loss) | |
| I0407 16:40:48.844501 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000152957 (* 0.0454545 = 6.95258e-06 loss) | |
| I0407 16:40:48.844516 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000171559 (* 0.0454545 = 7.79812e-06 loss) | |
| I0407 16:40:48.844530 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000172482 (* 0.0454545 = 7.84011e-06 loss) | |
| I0407 16:40:48.844544 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000171491 (* 0.0454545 = 7.79503e-06 loss) | |
| I0407 16:40:48.844574 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000187727 (* 0.0454545 = 8.53306e-06 loss) | |
| I0407 16:40:48.844605 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000179825 (* 0.0454545 = 8.17388e-06 loss) | |
| I0407 16:40:48.844620 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000151838 (* 0.0454545 = 6.90174e-06 loss) | |
| I0407 16:40:48.844635 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000172667 (* 0.0454545 = 7.84852e-06 loss) | |
| I0407 16:40:48.844650 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000181756 (* 0.0454545 = 8.26162e-06 loss) | |
| I0407 16:40:48.844663 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.00017146 (* 0.0454545 = 7.79364e-06 loss) | |
| I0407 16:40:48.844676 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:40:48.844687 1004 solver.cpp:245] Train net output #45: total_confidence = 1.55387e-06 | |
| I0407 16:40:48.844701 1004 sgd_solver.cpp:106] Iteration 65500, lr = 0.000869 | |
| I0407 16:41:27.845897 1004 solver.cpp:229] Iteration 66000, loss = 0.982354 | |
| I0407 16:41:27.846004 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 16:41:27.846025 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.125 | |
| I0407 16:41:27.846038 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:41:27.846051 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 16:41:27.846063 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.3125 | |
| I0407 16:41:27.846078 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5625 | |
| I0407 16:41:27.846091 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.875 | |
| I0407 16:41:27.846102 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 16:41:27.846114 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:41:27.846125 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:41:27.846146 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:41:27.846169 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:41:27.846186 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:41:27.846197 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:41:27.846210 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:41:27.846221 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:41:27.846232 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:41:27.846243 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:41:27.846256 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:41:27.846266 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:41:27.846278 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:41:27.846289 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:41:27.846305 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.48124 (* 0.0454545 = 0.158238 loss) | |
| I0407 16:41:27.846329 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.2511 (* 0.0454545 = 0.147777 loss) | |
| I0407 16:41:27.846354 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.57809 (* 0.0454545 = 0.16264 loss) | |
| I0407 16:41:27.846369 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.19601 (* 0.0454545 = 0.145273 loss) | |
| I0407 16:41:27.846382 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.17378 (* 0.0454545 = 0.144263 loss) | |
| I0407 16:41:27.846396 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.48128 (* 0.0454545 = 0.112786 loss) | |
| I0407 16:41:27.846410 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.863575 (* 0.0454545 = 0.0392534 loss) | |
| I0407 16:41:27.846424 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.807112 (* 0.0454545 = 0.0366869 loss) | |
| I0407 16:41:27.846438 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0151156 (* 0.0454545 = 0.000687073 loss) | |
| I0407 16:41:27.846452 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.00684207 (* 0.0454545 = 0.000311003 loss) | |
| I0407 16:41:27.846467 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000480169 (* 0.0454545 = 2.18259e-05 loss) | |
| I0407 16:41:27.846480 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000419156 (* 0.0454545 = 1.90525e-05 loss) | |
| I0407 16:41:27.846494 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000412567 (* 0.0454545 = 1.87531e-05 loss) | |
| I0407 16:41:27.846508 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000441631 (* 0.0454545 = 2.00741e-05 loss) | |
| I0407 16:41:27.846524 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000428365 (* 0.0454545 = 1.94711e-05 loss) | |
| I0407 16:41:27.846536 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000484768 (* 0.0454545 = 2.20349e-05 loss) | |
| I0407 16:41:27.846551 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000522853 (* 0.0454545 = 2.37661e-05 loss) | |
| I0407 16:41:27.846581 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000481629 (* 0.0454545 = 2.18922e-05 loss) | |
| I0407 16:41:27.846597 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000397647 (* 0.0454545 = 1.80749e-05 loss) | |
| I0407 16:41:27.846611 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000500923 (* 0.0454545 = 2.27692e-05 loss) | |
| I0407 16:41:27.846626 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000525984 (* 0.0454545 = 2.39084e-05 loss) | |
| I0407 16:41:27.846639 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000432202 (* 0.0454545 = 1.96455e-05 loss) | |
| I0407 16:41:27.846652 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:41:27.846663 1004 solver.cpp:245] Train net output #45: total_confidence = 3.29779e-06 | |
| I0407 16:41:27.846676 1004 sgd_solver.cpp:106] Iteration 66000, lr = 0.000868 | |
| I0407 16:42:07.261538 1004 solver.cpp:229] Iteration 66500, loss = 0.983326 | |
| I0407 16:42:07.261674 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:42:07.261695 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.125 | |
| I0407 16:42:07.261708 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.1875 | |
| I0407 16:42:07.261720 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 16:42:07.261732 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 16:42:07.261744 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 16:42:07.261756 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 16:42:07.261768 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:42:07.261780 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:42:07.261792 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 16:42:07.261804 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:42:07.261816 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:42:07.261827 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:42:07.261839 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:42:07.261852 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:42:07.261863 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:42:07.261874 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:42:07.261886 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:42:07.261898 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:42:07.261910 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:42:07.261925 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:42:07.261939 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:42:07.261955 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.22733 (* 0.0454545 = 0.146697 loss) | |
| I0407 16:42:07.261970 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.56939 (* 0.0454545 = 0.162245 loss) | |
| I0407 16:42:07.261983 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.45854 (* 0.0454545 = 0.157206 loss) | |
| I0407 16:42:07.261997 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.4058 (* 0.0454545 = 0.154809 loss) | |
| I0407 16:42:07.262012 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.35538 (* 0.0454545 = 0.152517 loss) | |
| I0407 16:42:07.262024 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.20073 (* 0.0454545 = 0.100033 loss) | |
| I0407 16:42:07.262038 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.97875 (* 0.0454545 = 0.0444887 loss) | |
| I0407 16:42:07.262053 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.360792 (* 0.0454545 = 0.0163996 loss) | |
| I0407 16:42:07.262066 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.376865 (* 0.0454545 = 0.0171302 loss) | |
| I0407 16:42:07.262080 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.609295 (* 0.0454545 = 0.0276952 loss) | |
| I0407 16:42:07.262095 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000164776 (* 0.0454545 = 7.48981e-06 loss) | |
| I0407 16:42:07.262109 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000148451 (* 0.0454545 = 6.74776e-06 loss) | |
| I0407 16:42:07.262123 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000144728 (* 0.0454545 = 6.57854e-06 loss) | |
| I0407 16:42:07.262137 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000164534 (* 0.0454545 = 7.47881e-06 loss) | |
| I0407 16:42:07.262151 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000173926 (* 0.0454545 = 7.90572e-06 loss) | |
| I0407 16:42:07.262166 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000172469 (* 0.0454545 = 7.8395e-06 loss) | |
| I0407 16:42:07.262181 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000166177 (* 0.0454545 = 7.55352e-06 loss) | |
| I0407 16:42:07.262210 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000173833 (* 0.0454545 = 7.9015e-06 loss) | |
| I0407 16:42:07.262226 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000179596 (* 0.0454545 = 8.16346e-06 loss) | |
| I0407 16:42:07.262240 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000168839 (* 0.0454545 = 7.67451e-06 loss) | |
| I0407 16:42:07.262254 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000187071 (* 0.0454545 = 8.50321e-06 loss) | |
| I0407 16:42:07.262269 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000195285 (* 0.0454545 = 8.87658e-06 loss) | |
| I0407 16:42:07.262280 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:42:07.262292 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000242682 | |
| I0407 16:42:07.262307 1004 sgd_solver.cpp:106] Iteration 66500, lr = 0.000867 | |
| I0407 16:42:47.489687 1004 solver.cpp:229] Iteration 67000, loss = 0.987158 | |
| I0407 16:42:47.489816 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:42:47.489835 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:42:47.489848 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:42:47.489861 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 16:42:47.489873 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.0625 | |
| I0407 16:42:47.489886 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 16:42:47.489897 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.625 | |
| I0407 16:42:47.489909 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:42:47.489926 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:42:47.489938 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:42:47.489950 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:42:47.489961 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:42:47.489974 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:42:47.489984 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:42:47.489996 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:42:47.490008 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:42:47.490020 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:42:47.490031 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:42:47.490042 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:42:47.490053 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:42:47.490066 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:42:47.490079 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:42:47.490095 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.71371 (* 0.0454545 = 0.168805 loss) | |
| I0407 16:42:47.490110 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.83365 (* 0.0454545 = 0.174257 loss) | |
| I0407 16:42:47.490124 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.78567 (* 0.0454545 = 0.172076 loss) | |
| I0407 16:42:47.490137 1004 solver.cpp:245] Train net output #25: loss/loss04 = 4.00524 (* 0.0454545 = 0.182056 loss) | |
| I0407 16:42:47.490151 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.83326 (* 0.0454545 = 0.174239 loss) | |
| I0407 16:42:47.490165 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.01783 (* 0.0454545 = 0.137174 loss) | |
| I0407 16:42:47.490180 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.94207 (* 0.0454545 = 0.088276 loss) | |
| I0407 16:42:47.490193 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.531304 (* 0.0454545 = 0.0241502 loss) | |
| I0407 16:42:47.490207 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0232303 (* 0.0454545 = 0.00105592 loss) | |
| I0407 16:42:47.490221 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0111908 (* 0.0454545 = 0.000508671 loss) | |
| I0407 16:42:47.490236 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000544018 (* 0.0454545 = 2.47281e-05 loss) | |
| I0407 16:42:47.490250 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000479453 (* 0.0454545 = 2.17933e-05 loss) | |
| I0407 16:42:47.490264 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000466757 (* 0.0454545 = 2.12162e-05 loss) | |
| I0407 16:42:47.490278 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000539559 (* 0.0454545 = 2.45254e-05 loss) | |
| I0407 16:42:47.490293 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000519863 (* 0.0454545 = 2.36302e-05 loss) | |
| I0407 16:42:47.490308 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000472787 (* 0.0454545 = 2.14903e-05 loss) | |
| I0407 16:42:47.490321 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.00054274 (* 0.0454545 = 2.467e-05 loss) | |
| I0407 16:42:47.490348 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000520774 (* 0.0454545 = 2.36716e-05 loss) | |
| I0407 16:42:47.490363 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000498936 (* 0.0454545 = 2.26789e-05 loss) | |
| I0407 16:42:47.490377 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000460697 (* 0.0454545 = 2.09408e-05 loss) | |
| I0407 16:42:47.490392 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000507112 (* 0.0454545 = 2.30505e-05 loss) | |
| I0407 16:42:47.490406 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000455935 (* 0.0454545 = 2.07243e-05 loss) | |
| I0407 16:42:47.490417 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:42:47.490429 1004 solver.cpp:245] Train net output #45: total_confidence = 5.95702e-06 | |
| I0407 16:42:47.490442 1004 sgd_solver.cpp:106] Iteration 67000, lr = 0.000866 | |
| I0407 16:43:26.774057 1004 solver.cpp:229] Iteration 67500, loss = 0.984098 | |
| I0407 16:43:26.774204 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:43:26.774224 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:43:26.774237 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:43:26.774250 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 16:43:26.774261 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 16:43:26.774273 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 16:43:26.774286 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 16:43:26.774297 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 16:43:26.774309 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:43:26.774322 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:43:26.774333 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:43:26.774344 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:43:26.774356 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:43:26.774368 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:43:26.774379 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:43:26.774391 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:43:26.774402 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:43:26.774415 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:43:26.774426 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:43:26.774437 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:43:26.774449 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:43:26.774461 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:43:26.774477 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.56135 (* 0.0454545 = 0.161879 loss) | |
| I0407 16:43:26.774490 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.9947 (* 0.0454545 = 0.181578 loss) | |
| I0407 16:43:26.774504 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.94002 (* 0.0454545 = 0.179092 loss) | |
| I0407 16:43:26.774518 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.95755 (* 0.0454545 = 0.179889 loss) | |
| I0407 16:43:26.774533 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.8276 (* 0.0454545 = 0.173982 loss) | |
| I0407 16:43:26.774547 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.6489 (* 0.0454545 = 0.120405 loss) | |
| I0407 16:43:26.774561 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.31857 (* 0.0454545 = 0.0599348 loss) | |
| I0407 16:43:26.774575 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.7945 (* 0.0454545 = 0.0361136 loss) | |
| I0407 16:43:26.774588 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.368153 (* 0.0454545 = 0.0167342 loss) | |
| I0407 16:43:26.774603 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0146493 (* 0.0454545 = 0.000665878 loss) | |
| I0407 16:43:26.774617 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000408842 (* 0.0454545 = 1.85837e-05 loss) | |
| I0407 16:43:26.774632 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000343928 (* 0.0454545 = 1.56331e-05 loss) | |
| I0407 16:43:26.774646 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.00034485 (* 0.0454545 = 1.5675e-05 loss) | |
| I0407 16:43:26.774662 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.00037349 (* 0.0454545 = 1.69768e-05 loss) | |
| I0407 16:43:26.774675 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000389883 (* 0.0454545 = 1.7722e-05 loss) | |
| I0407 16:43:26.774689 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000369353 (* 0.0454545 = 1.67888e-05 loss) | |
| I0407 16:43:26.774704 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000448523 (* 0.0454545 = 2.03874e-05 loss) | |
| I0407 16:43:26.774735 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000452177 (* 0.0454545 = 2.05535e-05 loss) | |
| I0407 16:43:26.774750 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000374097 (* 0.0454545 = 1.70044e-05 loss) | |
| I0407 16:43:26.774765 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000375683 (* 0.0454545 = 1.70765e-05 loss) | |
| I0407 16:43:26.774778 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000454098 (* 0.0454545 = 2.06408e-05 loss) | |
| I0407 16:43:26.774792 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000380017 (* 0.0454545 = 1.72735e-05 loss) | |
| I0407 16:43:26.774804 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:43:26.774816 1004 solver.cpp:245] Train net output #45: total_confidence = 4.88729e-05 | |
| I0407 16:43:26.774829 1004 sgd_solver.cpp:106] Iteration 67500, lr = 0.000865 | |
| I0407 16:44:05.786052 1004 solver.cpp:229] Iteration 68000, loss = 0.975454 | |
| I0407 16:44:05.786157 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 16:44:05.786176 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.125 | |
| I0407 16:44:05.786190 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:44:05.786202 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 16:44:05.786214 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 16:44:05.786226 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 16:44:05.786238 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 16:44:05.786250 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 16:44:05.786262 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:44:05.786274 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:44:05.786285 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:44:05.786298 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:44:05.786309 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:44:05.786320 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:44:05.786331 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:44:05.786344 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:44:05.786355 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:44:05.786366 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:44:05.786377 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:44:05.786389 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:44:05.786401 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:44:05.786412 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:44:05.786427 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.81166 (* 0.0454545 = 0.173257 loss) | |
| I0407 16:44:05.786442 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.4425 (* 0.0454545 = 0.156477 loss) | |
| I0407 16:44:05.786456 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.67447 (* 0.0454545 = 0.167021 loss) | |
| I0407 16:44:05.786470 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.95792 (* 0.0454545 = 0.179905 loss) | |
| I0407 16:44:05.786484 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.99199 (* 0.0454545 = 0.181454 loss) | |
| I0407 16:44:05.786499 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.46541 (* 0.0454545 = 0.112064 loss) | |
| I0407 16:44:05.786512 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.78125 (* 0.0454545 = 0.0809658 loss) | |
| I0407 16:44:05.786525 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.25353 (* 0.0454545 = 0.0569787 loss) | |
| I0407 16:44:05.786540 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0296443 (* 0.0454545 = 0.00134747 loss) | |
| I0407 16:44:05.786555 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0128777 (* 0.0454545 = 0.00058535 loss) | |
| I0407 16:44:05.786568 1004 solver.cpp:245] Train net output #32: loss/loss11 = 9.21634e-05 (* 0.0454545 = 4.18925e-06 loss) | |
| I0407 16:44:05.786583 1004 solver.cpp:245] Train net output #33: loss/loss12 = 6.90323e-05 (* 0.0454545 = 3.13783e-06 loss) | |
| I0407 16:44:05.786597 1004 solver.cpp:245] Train net output #34: loss/loss13 = 8.24181e-05 (* 0.0454545 = 3.74628e-06 loss) | |
| I0407 16:44:05.786612 1004 solver.cpp:245] Train net output #35: loss/loss14 = 9.01811e-05 (* 0.0454545 = 4.09914e-06 loss) | |
| I0407 16:44:05.786625 1004 solver.cpp:245] Train net output #36: loss/loss15 = 9.12806e-05 (* 0.0454545 = 4.14912e-06 loss) | |
| I0407 16:44:05.786639 1004 solver.cpp:245] Train net output #37: loss/loss16 = 7.99681e-05 (* 0.0454545 = 3.63491e-06 loss) | |
| I0407 16:44:05.786653 1004 solver.cpp:245] Train net output #38: loss/loss17 = 9.3215e-05 (* 0.0454545 = 4.23704e-06 loss) | |
| I0407 16:44:05.786684 1004 solver.cpp:245] Train net output #39: loss/loss18 = 9.62554e-05 (* 0.0454545 = 4.37525e-06 loss) | |
| I0407 16:44:05.786700 1004 solver.cpp:245] Train net output #40: loss/loss19 = 7.98163e-05 (* 0.0454545 = 3.62801e-06 loss) | |
| I0407 16:44:05.786713 1004 solver.cpp:245] Train net output #41: loss/loss20 = 8.6271e-05 (* 0.0454545 = 3.92141e-06 loss) | |
| I0407 16:44:05.786728 1004 solver.cpp:245] Train net output #42: loss/loss21 = 9.02412e-05 (* 0.0454545 = 4.10187e-06 loss) | |
| I0407 16:44:05.786742 1004 solver.cpp:245] Train net output #43: loss/loss22 = 9.66956e-05 (* 0.0454545 = 4.39526e-06 loss) | |
| I0407 16:44:05.786754 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:44:05.786767 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000115648 | |
| I0407 16:44:05.786779 1004 sgd_solver.cpp:106] Iteration 68000, lr = 0.000864 | |
| I0407 16:44:45.386806 1004 solver.cpp:229] Iteration 68500, loss = 0.984466 | |
| I0407 16:44:45.386927 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:44:45.386947 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:44:45.386960 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 16:44:45.386973 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 16:44:45.386986 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.0625 | |
| I0407 16:44:45.386997 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.25 | |
| I0407 16:44:45.387009 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.4375 | |
| I0407 16:44:45.387022 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.6875 | |
| I0407 16:44:45.387034 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:44:45.387047 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:44:45.387058 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:44:45.387069 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:44:45.387080 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:44:45.387092 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:44:45.387104 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:44:45.387115 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:44:45.387126 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:44:45.387138 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:44:45.387150 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:44:45.387161 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:44:45.387172 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:44:45.387183 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:44:45.387199 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.36783 (* 0.0454545 = 0.153083 loss) | |
| I0407 16:44:45.387213 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.4958 (* 0.0454545 = 0.1589 loss) | |
| I0407 16:44:45.387228 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.36372 (* 0.0454545 = 0.152896 loss) | |
| I0407 16:44:45.387241 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.22322 (* 0.0454545 = 0.14651 loss) | |
| I0407 16:44:45.387255 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.68578 (* 0.0454545 = 0.167535 loss) | |
| I0407 16:44:45.387269 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.02132 (* 0.0454545 = 0.137333 loss) | |
| I0407 16:44:45.387284 1004 solver.cpp:245] Train net output #28: loss/loss07 = 2.87355 (* 0.0454545 = 0.130616 loss) | |
| I0407 16:44:45.387296 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.7943 (* 0.0454545 = 0.0815593 loss) | |
| I0407 16:44:45.387311 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0388893 (* 0.0454545 = 0.00176769 loss) | |
| I0407 16:44:45.387341 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0140929 (* 0.0454545 = 0.000640586 loss) | |
| I0407 16:44:45.387358 1004 solver.cpp:245] Train net output #32: loss/loss11 = 3.91067e-05 (* 0.0454545 = 1.77758e-06 loss) | |
| I0407 16:44:45.387372 1004 solver.cpp:245] Train net output #33: loss/loss12 = 3.48763e-05 (* 0.0454545 = 1.58529e-06 loss) | |
| I0407 16:44:45.387387 1004 solver.cpp:245] Train net output #34: loss/loss13 = 3.08104e-05 (* 0.0454545 = 1.40047e-06 loss) | |
| I0407 16:44:45.387401 1004 solver.cpp:245] Train net output #35: loss/loss14 = 3.83465e-05 (* 0.0454545 = 1.74302e-06 loss) | |
| I0407 16:44:45.387415 1004 solver.cpp:245] Train net output #36: loss/loss15 = 3.88684e-05 (* 0.0454545 = 1.76675e-06 loss) | |
| I0407 16:44:45.387429 1004 solver.cpp:245] Train net output #37: loss/loss16 = 3.99976e-05 (* 0.0454545 = 1.81807e-06 loss) | |
| I0407 16:44:45.387444 1004 solver.cpp:245] Train net output #38: loss/loss17 = 3.80858e-05 (* 0.0454545 = 1.73117e-06 loss) | |
| I0407 16:44:45.387475 1004 solver.cpp:245] Train net output #39: loss/loss18 = 3.78545e-05 (* 0.0454545 = 1.72066e-06 loss) | |
| I0407 16:44:45.387491 1004 solver.cpp:245] Train net output #40: loss/loss19 = 3.1854e-05 (* 0.0454545 = 1.44791e-06 loss) | |
| I0407 16:44:45.387506 1004 solver.cpp:245] Train net output #41: loss/loss20 = 3.15708e-05 (* 0.0454545 = 1.43504e-06 loss) | |
| I0407 16:44:45.387519 1004 solver.cpp:245] Train net output #42: loss/loss21 = 3.93084e-05 (* 0.0454545 = 1.78674e-06 loss) | |
| I0407 16:44:45.387533 1004 solver.cpp:245] Train net output #43: loss/loss22 = 3.53908e-05 (* 0.0454545 = 1.60867e-06 loss) | |
| I0407 16:44:45.387545 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:44:45.387557 1004 solver.cpp:245] Train net output #45: total_confidence = 9.40113e-05 | |
| I0407 16:44:45.387570 1004 sgd_solver.cpp:106] Iteration 68500, lr = 0.000863 | |
| I0407 16:45:24.637388 1004 solver.cpp:229] Iteration 69000, loss = 0.985722 | |
| I0407 16:45:24.637650 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0407 16:45:24.637670 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:45:24.637683 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:45:24.637696 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 16:45:24.637708 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 16:45:24.637720 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.25 | |
| I0407 16:45:24.637732 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.9375 | |
| I0407 16:45:24.637744 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 16:45:24.637756 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:45:24.637768 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:45:24.637779 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:45:24.637791 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:45:24.637802 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:45:24.637814 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:45:24.637826 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:45:24.637837 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:45:24.637850 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:45:24.637861 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:45:24.637872 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:45:24.637883 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:45:24.637895 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:45:24.637907 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:45:24.637925 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.29199 (* 0.0454545 = 0.149636 loss) | |
| I0407 16:45:24.637940 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.41292 (* 0.0454545 = 0.155133 loss) | |
| I0407 16:45:24.637954 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.60354 (* 0.0454545 = 0.163797 loss) | |
| I0407 16:45:24.637969 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.17367 (* 0.0454545 = 0.144258 loss) | |
| I0407 16:45:24.637981 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.32073 (* 0.0454545 = 0.150942 loss) | |
| I0407 16:45:24.637995 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.1574 (* 0.0454545 = 0.143518 loss) | |
| I0407 16:45:24.638010 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.542803 (* 0.0454545 = 0.0246729 loss) | |
| I0407 16:45:24.638023 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.0833006 (* 0.0454545 = 0.00378639 loss) | |
| I0407 16:45:24.638037 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0290713 (* 0.0454545 = 0.00132142 loss) | |
| I0407 16:45:24.638051 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0115152 (* 0.0454545 = 0.000523417 loss) | |
| I0407 16:45:24.638065 1004 solver.cpp:245] Train net output #32: loss/loss11 = 1.6985e-05 (* 0.0454545 = 7.72046e-07 loss) | |
| I0407 16:45:24.638079 1004 solver.cpp:245] Train net output #33: loss/loss12 = 1.36765e-05 (* 0.0454545 = 6.21659e-07 loss) | |
| I0407 16:45:24.638093 1004 solver.cpp:245] Train net output #34: loss/loss13 = 1.29574e-05 (* 0.0454545 = 5.88972e-07 loss) | |
| I0407 16:45:24.638108 1004 solver.cpp:245] Train net output #35: loss/loss14 = 1.22643e-05 (* 0.0454545 = 5.5747e-07 loss) | |
| I0407 16:45:24.638121 1004 solver.cpp:245] Train net output #36: loss/loss15 = 1.27711e-05 (* 0.0454545 = 5.80503e-07 loss) | |
| I0407 16:45:24.638135 1004 solver.cpp:245] Train net output #37: loss/loss16 = 1.39224e-05 (* 0.0454545 = 6.32835e-07 loss) | |
| I0407 16:45:24.638150 1004 solver.cpp:245] Train net output #38: loss/loss17 = 1.29648e-05 (* 0.0454545 = 5.89308e-07 loss) | |
| I0407 16:45:24.638178 1004 solver.cpp:245] Train net output #39: loss/loss18 = 1.44514e-05 (* 0.0454545 = 6.56883e-07 loss) | |
| I0407 16:45:24.638193 1004 solver.cpp:245] Train net output #40: loss/loss19 = 1.13255e-05 (* 0.0454545 = 5.14794e-07 loss) | |
| I0407 16:45:24.638207 1004 solver.cpp:245] Train net output #41: loss/loss20 = 1.2093e-05 (* 0.0454545 = 5.49684e-07 loss) | |
| I0407 16:45:24.638221 1004 solver.cpp:245] Train net output #42: loss/loss21 = 1.21228e-05 (* 0.0454545 = 5.51035e-07 loss) | |
| I0407 16:45:24.638236 1004 solver.cpp:245] Train net output #43: loss/loss22 = 1.31437e-05 (* 0.0454545 = 5.97439e-07 loss) | |
| I0407 16:45:24.638247 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:45:24.638258 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000216036 | |
| I0407 16:45:24.638272 1004 sgd_solver.cpp:106] Iteration 69000, lr = 0.000862 | |
| I0407 16:46:04.116844 1004 solver.cpp:229] Iteration 69500, loss = 0.987112 | |
| I0407 16:46:04.116950 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.1875 | |
| I0407 16:46:04.116969 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:46:04.116983 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:46:04.116996 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 16:46:04.117007 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 16:46:04.117019 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 16:46:04.117032 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 16:46:04.117043 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 16:46:04.117055 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:46:04.117068 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:46:04.117081 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:46:04.117094 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:46:04.117105 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:46:04.117117 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:46:04.117130 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:46:04.117141 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:46:04.117152 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:46:04.117163 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:46:04.117175 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:46:04.117187 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:46:04.117197 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:46:04.117209 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:46:04.117225 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.51719 (* 0.0454545 = 0.159872 loss) | |
| I0407 16:46:04.117239 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.98629 (* 0.0454545 = 0.181195 loss) | |
| I0407 16:46:04.117254 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.9516 (* 0.0454545 = 0.179618 loss) | |
| I0407 16:46:04.117267 1004 solver.cpp:245] Train net output #25: loss/loss04 = 4.20139 (* 0.0454545 = 0.190972 loss) | |
| I0407 16:46:04.117281 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.56748 (* 0.0454545 = 0.162158 loss) | |
| I0407 16:46:04.117295 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.47257 (* 0.0454545 = 0.11239 loss) | |
| I0407 16:46:04.117308 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.09127 (* 0.0454545 = 0.0496033 loss) | |
| I0407 16:46:04.117322 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.665086 (* 0.0454545 = 0.0302312 loss) | |
| I0407 16:46:04.117336 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0217572 (* 0.0454545 = 0.000988962 loss) | |
| I0407 16:46:04.117350 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.00825213 (* 0.0454545 = 0.000375097 loss) | |
| I0407 16:46:04.117365 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000356817 (* 0.0454545 = 1.6219e-05 loss) | |
| I0407 16:46:04.117379 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000292235 (* 0.0454545 = 1.32834e-05 loss) | |
| I0407 16:46:04.117393 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000286858 (* 0.0454545 = 1.3039e-05 loss) | |
| I0407 16:46:04.117408 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000310597 (* 0.0454545 = 1.4118e-05 loss) | |
| I0407 16:46:04.117422 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000349337 (* 0.0454545 = 1.5879e-05 loss) | |
| I0407 16:46:04.117436 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000324802 (* 0.0454545 = 1.47637e-05 loss) | |
| I0407 16:46:04.117450 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000340583 (* 0.0454545 = 1.54811e-05 loss) | |
| I0407 16:46:04.117482 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000339137 (* 0.0454545 = 1.54153e-05 loss) | |
| I0407 16:46:04.117498 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000320974 (* 0.0454545 = 1.45897e-05 loss) | |
| I0407 16:46:04.117512 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000316893 (* 0.0454545 = 1.44042e-05 loss) | |
| I0407 16:46:04.117527 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00034437 (* 0.0454545 = 1.56532e-05 loss) | |
| I0407 16:46:04.117540 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000345477 (* 0.0454545 = 1.57035e-05 loss) | |
| I0407 16:46:04.117552 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:46:04.117563 1004 solver.cpp:245] Train net output #45: total_confidence = 2.4211e-05 | |
| I0407 16:46:04.117578 1004 sgd_solver.cpp:106] Iteration 69500, lr = 0.000861 | |
| I0407 16:46:44.526106 1004 solver.cpp:338] Iteration 70000, Testing net (#0) | |
| I0407 16:46:52.460484 1004 solver.cpp:393] Test loss: 0.888049 | |
| I0407 16:46:52.460530 1004 solver.cpp:406] Test net output #0: loss/accuracy01 = 0.324 | |
| I0407 16:46:52.460546 1004 solver.cpp:406] Test net output #1: loss/accuracy02 = 0.113 | |
| I0407 16:46:52.460558 1004 solver.cpp:406] Test net output #2: loss/accuracy03 = 0.072 | |
| I0407 16:46:52.460571 1004 solver.cpp:406] Test net output #3: loss/accuracy04 = 0.087 | |
| I0407 16:46:52.460582 1004 solver.cpp:406] Test net output #4: loss/accuracy05 = 0.203 | |
| I0407 16:46:52.460594 1004 solver.cpp:406] Test net output #5: loss/accuracy06 = 0.493 | |
| I0407 16:46:52.460605 1004 solver.cpp:406] Test net output #6: loss/accuracy07 = 0.893 | |
| I0407 16:46:52.460618 1004 solver.cpp:406] Test net output #7: loss/accuracy08 = 0.97 | |
| I0407 16:46:52.460628 1004 solver.cpp:406] Test net output #8: loss/accuracy09 = 0.995 | |
| I0407 16:46:52.460639 1004 solver.cpp:406] Test net output #9: loss/accuracy10 = 0.998 | |
| I0407 16:46:52.460651 1004 solver.cpp:406] Test net output #10: loss/accuracy11 = 1 | |
| I0407 16:46:52.460662 1004 solver.cpp:406] Test net output #11: loss/accuracy12 = 1 | |
| I0407 16:46:52.460674 1004 solver.cpp:406] Test net output #12: loss/accuracy13 = 1 | |
| I0407 16:46:52.460685 1004 solver.cpp:406] Test net output #13: loss/accuracy14 = 1 | |
| I0407 16:46:52.460695 1004 solver.cpp:406] Test net output #14: loss/accuracy15 = 1 | |
| I0407 16:46:52.460706 1004 solver.cpp:406] Test net output #15: loss/accuracy16 = 1 | |
| I0407 16:46:52.460717 1004 solver.cpp:406] Test net output #16: loss/accuracy17 = 1 | |
| I0407 16:46:52.460728 1004 solver.cpp:406] Test net output #17: loss/accuracy18 = 1 | |
| I0407 16:46:52.460739 1004 solver.cpp:406] Test net output #18: loss/accuracy19 = 1 | |
| I0407 16:46:52.460752 1004 solver.cpp:406] Test net output #19: loss/accuracy20 = 1 | |
| I0407 16:46:52.460763 1004 solver.cpp:406] Test net output #20: loss/accuracy21 = 1 | |
| I0407 16:46:52.460774 1004 solver.cpp:406] Test net output #21: loss/accuracy22 = 1 | |
| I0407 16:46:52.460789 1004 solver.cpp:406] Test net output #22: loss/loss01 = 3.08629 (* 0.0454545 = 0.140286 loss) | |
| I0407 16:46:52.460803 1004 solver.cpp:406] Test net output #23: loss/loss02 = 3.22897 (* 0.0454545 = 0.146771 loss) | |
| I0407 16:46:52.460818 1004 solver.cpp:406] Test net output #24: loss/loss03 = 3.35784 (* 0.0454545 = 0.152629 loss) | |
| I0407 16:46:52.460831 1004 solver.cpp:406] Test net output #25: loss/loss04 = 3.2942 (* 0.0454545 = 0.149737 loss) | |
| I0407 16:46:52.460844 1004 solver.cpp:406] Test net output #26: loss/loss05 = 3.2085 (* 0.0454545 = 0.145841 loss) | |
| I0407 16:46:52.460858 1004 solver.cpp:406] Test net output #27: loss/loss06 = 2.27187 (* 0.0454545 = 0.103267 loss) | |
| I0407 16:46:52.460871 1004 solver.cpp:406] Test net output #28: loss/loss07 = 0.741074 (* 0.0454545 = 0.0336852 loss) | |
| I0407 16:46:52.460886 1004 solver.cpp:406] Test net output #29: loss/loss08 = 0.255635 (* 0.0454545 = 0.0116198 loss) | |
| I0407 16:46:52.460899 1004 solver.cpp:406] Test net output #30: loss/loss09 = 0.0592638 (* 0.0454545 = 0.00269381 loss) | |
| I0407 16:46:52.460913 1004 solver.cpp:406] Test net output #31: loss/loss10 = 0.030532 (* 0.0454545 = 0.00138782 loss) | |
| I0407 16:46:52.460927 1004 solver.cpp:406] Test net output #32: loss/loss11 = 0.000261337 (* 0.0454545 = 1.18789e-05 loss) | |
| I0407 16:46:52.460942 1004 solver.cpp:406] Test net output #33: loss/loss12 = 0.000231779 (* 0.0454545 = 1.05354e-05 loss) | |
| I0407 16:46:52.460955 1004 solver.cpp:406] Test net output #34: loss/loss13 = 0.000231865 (* 0.0454545 = 1.05393e-05 loss) | |
| I0407 16:46:52.460969 1004 solver.cpp:406] Test net output #35: loss/loss14 = 0.000244735 (* 0.0454545 = 1.11243e-05 loss) | |
| I0407 16:46:52.460988 1004 solver.cpp:406] Test net output #36: loss/loss15 = 0.000248162 (* 0.0454545 = 1.12801e-05 loss) | |
| I0407 16:46:52.461001 1004 solver.cpp:406] Test net output #37: loss/loss16 = 0.000225716 (* 0.0454545 = 1.02598e-05 loss) | |
| I0407 16:46:52.461015 1004 solver.cpp:406] Test net output #38: loss/loss17 = 0.000253076 (* 0.0454545 = 1.15034e-05 loss) | |
| I0407 16:46:52.461066 1004 solver.cpp:406] Test net output #39: loss/loss18 = 0.000268342 (* 0.0454545 = 1.21974e-05 loss) | |
| I0407 16:46:52.461081 1004 solver.cpp:406] Test net output #40: loss/loss19 = 0.000233735 (* 0.0454545 = 1.06243e-05 loss) | |
| I0407 16:46:52.461094 1004 solver.cpp:406] Test net output #41: loss/loss20 = 0.000229244 (* 0.0454545 = 1.04202e-05 loss) | |
| I0407 16:46:52.461107 1004 solver.cpp:406] Test net output #42: loss/loss21 = 0.000250655 (* 0.0454545 = 1.13934e-05 loss) | |
| I0407 16:46:52.461122 1004 solver.cpp:406] Test net output #43: loss/loss22 = 0.000233167 (* 0.0454545 = 1.05985e-05 loss) | |
| I0407 16:46:52.461133 1004 solver.cpp:406] Test net output #44: total_accuracy = 0 | |
| I0407 16:46:52.461144 1004 solver.cpp:406] Test net output #45: total_confidence = 0.000117004 | |
| I0407 16:46:52.483754 1004 solver.cpp:229] Iteration 70000, loss = 0.984851 | |
| I0407 16:46:52.483799 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.1875 | |
| I0407 16:46:52.483815 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:46:52.483829 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 16:46:52.483841 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 16:46:52.483857 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.375 | |
| I0407 16:46:52.483870 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5 | |
| I0407 16:46:52.483881 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 16:46:52.483896 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:46:52.483914 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:46:52.483927 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:46:52.483938 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:46:52.483949 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:46:52.483961 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:46:52.483973 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:46:52.483984 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:46:52.483995 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:46:52.484006 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:46:52.484019 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:46:52.484031 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:46:52.484042 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:46:52.484053 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:46:52.484066 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:46:52.484082 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.65235 (* 0.0454545 = 0.166016 loss) | |
| I0407 16:46:52.484097 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.78133 (* 0.0454545 = 0.171879 loss) | |
| I0407 16:46:52.484110 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.79312 (* 0.0454545 = 0.172415 loss) | |
| I0407 16:46:52.484124 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.5548 (* 0.0454545 = 0.161582 loss) | |
| I0407 16:46:52.484138 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.06015 (* 0.0454545 = 0.139098 loss) | |
| I0407 16:46:52.484151 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.46314 (* 0.0454545 = 0.111961 loss) | |
| I0407 16:46:52.484165 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.50087 (* 0.0454545 = 0.0682213 loss) | |
| I0407 16:46:52.484179 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.914252 (* 0.0454545 = 0.0415569 loss) | |
| I0407 16:46:52.484194 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0864355 (* 0.0454545 = 0.00392889 loss) | |
| I0407 16:46:52.484207 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0326498 (* 0.0454545 = 0.00148408 loss) | |
| I0407 16:46:52.484239 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000151755 (* 0.0454545 = 6.89796e-06 loss) | |
| I0407 16:46:52.484254 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000152871 (* 0.0454545 = 6.94868e-06 loss) | |
| I0407 16:46:52.484268 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000142879 (* 0.0454545 = 6.4945e-06 loss) | |
| I0407 16:46:52.484283 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000169099 (* 0.0454545 = 7.68633e-06 loss) | |
| I0407 16:46:52.484297 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000169297 (* 0.0454545 = 7.6953e-06 loss) | |
| I0407 16:46:52.484310 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000145471 (* 0.0454545 = 6.61231e-06 loss) | |
| I0407 16:46:52.484324 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000160957 (* 0.0454545 = 7.31624e-06 loss) | |
| I0407 16:46:52.484338 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000170365 (* 0.0454545 = 7.74384e-06 loss) | |
| I0407 16:46:52.484352 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000146848 (* 0.0454545 = 6.67492e-06 loss) | |
| I0407 16:46:52.484366 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000147107 (* 0.0454545 = 6.68668e-06 loss) | |
| I0407 16:46:52.484380 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.0001544 (* 0.0454545 = 7.0182e-06 loss) | |
| I0407 16:46:52.484395 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000143109 (* 0.0454545 = 6.50493e-06 loss) | |
| I0407 16:46:52.484406 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:46:52.484417 1004 solver.cpp:245] Train net output #45: total_confidence = 4.78303e-05 | |
| I0407 16:46:52.484432 1004 sgd_solver.cpp:106] Iteration 70000, lr = 0.00086 | |
| I0407 16:47:31.608580 1004 solver.cpp:229] Iteration 70500, loss = 0.986425 | |
| I0407 16:47:31.608758 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:47:31.608779 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:47:31.608793 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:47:31.608805 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 16:47:31.608817 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 16:47:31.608829 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 16:47:31.608841 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 16:47:31.608853 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 16:47:31.608865 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.875 | |
| I0407 16:47:31.608876 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 16:47:31.608888 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:47:31.608901 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:47:31.608911 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:47:31.608923 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:47:31.608934 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:47:31.608947 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:47:31.608958 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:47:31.608969 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:47:31.608980 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:47:31.608991 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:47:31.609004 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:47:31.609014 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:47:31.609030 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.94627 (* 0.0454545 = 0.179376 loss) | |
| I0407 16:47:31.609045 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.86089 (* 0.0454545 = 0.175495 loss) | |
| I0407 16:47:31.609058 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.98279 (* 0.0454545 = 0.181036 loss) | |
| I0407 16:47:31.609076 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.83832 (* 0.0454545 = 0.174469 loss) | |
| I0407 16:47:31.609091 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.74897 (* 0.0454545 = 0.170408 loss) | |
| I0407 16:47:31.609104 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.21764 (* 0.0454545 = 0.146256 loss) | |
| I0407 16:47:31.609118 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.90324 (* 0.0454545 = 0.0865107 loss) | |
| I0407 16:47:31.609132 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.42332 (* 0.0454545 = 0.0646963 loss) | |
| I0407 16:47:31.609145 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.914857 (* 0.0454545 = 0.0415844 loss) | |
| I0407 16:47:31.609158 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.634297 (* 0.0454545 = 0.0288317 loss) | |
| I0407 16:47:31.609174 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000577601 (* 0.0454545 = 2.62546e-05 loss) | |
| I0407 16:47:31.609187 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00054958 (* 0.0454545 = 2.49809e-05 loss) | |
| I0407 16:47:31.609201 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000487632 (* 0.0454545 = 2.21651e-05 loss) | |
| I0407 16:47:31.609215 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000507819 (* 0.0454545 = 2.30827e-05 loss) | |
| I0407 16:47:31.609230 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000518771 (* 0.0454545 = 2.35805e-05 loss) | |
| I0407 16:47:31.609246 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000492006 (* 0.0454545 = 2.23639e-05 loss) | |
| I0407 16:47:31.609272 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000564126 (* 0.0454545 = 2.56421e-05 loss) | |
| I0407 16:47:31.609308 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000497806 (* 0.0454545 = 2.26275e-05 loss) | |
| I0407 16:47:31.609324 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00054782 (* 0.0454545 = 2.49009e-05 loss) | |
| I0407 16:47:31.609338 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.00050767 (* 0.0454545 = 2.30759e-05 loss) | |
| I0407 16:47:31.609352 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000515307 (* 0.0454545 = 2.34231e-05 loss) | |
| I0407 16:47:31.609370 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000485694 (* 0.0454545 = 2.2077e-05 loss) | |
| I0407 16:47:31.609383 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:47:31.609395 1004 solver.cpp:245] Train net output #45: total_confidence = 1.61228e-06 | |
| I0407 16:47:31.609410 1004 sgd_solver.cpp:106] Iteration 70500, lr = 0.000859 | |
| I0407 16:48:10.825930 1004 solver.cpp:229] Iteration 71000, loss = 0.977451 | |
| I0407 16:48:10.826061 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:48:10.826079 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.125 | |
| I0407 16:48:10.826092 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:48:10.826104 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 16:48:10.826117 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.3125 | |
| I0407 16:48:10.826128 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 16:48:10.826140 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 16:48:10.826151 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:48:10.826164 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:48:10.826175 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 16:48:10.826186 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:48:10.826198 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:48:10.826210 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:48:10.826221 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:48:10.826232 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:48:10.826244 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:48:10.826256 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:48:10.826267 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:48:10.826279 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:48:10.826290 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:48:10.826302 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:48:10.826313 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:48:10.826329 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.02945 (* 0.0454545 = 0.137702 loss) | |
| I0407 16:48:10.826344 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.45144 (* 0.0454545 = 0.156884 loss) | |
| I0407 16:48:10.826359 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.55654 (* 0.0454545 = 0.161661 loss) | |
| I0407 16:48:10.826372 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.32121 (* 0.0454545 = 0.150964 loss) | |
| I0407 16:48:10.826386 1004 solver.cpp:245] Train net output #26: loss/loss05 = 2.98084 (* 0.0454545 = 0.135493 loss) | |
| I0407 16:48:10.826400 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.5713 (* 0.0454545 = 0.116877 loss) | |
| I0407 16:48:10.826414 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.3652 (* 0.0454545 = 0.0620545 loss) | |
| I0407 16:48:10.826428 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.388642 (* 0.0454545 = 0.0176656 loss) | |
| I0407 16:48:10.826442 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.366757 (* 0.0454545 = 0.0166708 loss) | |
| I0407 16:48:10.826457 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.40284 (* 0.0454545 = 0.0183109 loss) | |
| I0407 16:48:10.826470 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000447545 (* 0.0454545 = 2.03429e-05 loss) | |
| I0407 16:48:10.826484 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00039289 (* 0.0454545 = 1.78587e-05 loss) | |
| I0407 16:48:10.826498 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000400319 (* 0.0454545 = 1.81963e-05 loss) | |
| I0407 16:48:10.826513 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000447868 (* 0.0454545 = 2.03576e-05 loss) | |
| I0407 16:48:10.826526 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000523369 (* 0.0454545 = 2.37895e-05 loss) | |
| I0407 16:48:10.826540 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000418314 (* 0.0454545 = 1.90143e-05 loss) | |
| I0407 16:48:10.826555 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000490725 (* 0.0454545 = 2.23057e-05 loss) | |
| I0407 16:48:10.826586 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000496548 (* 0.0454545 = 2.25704e-05 loss) | |
| I0407 16:48:10.826601 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000410911 (* 0.0454545 = 1.86778e-05 loss) | |
| I0407 16:48:10.826616 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000415842 (* 0.0454545 = 1.89019e-05 loss) | |
| I0407 16:48:10.826629 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00046412 (* 0.0454545 = 2.10964e-05 loss) | |
| I0407 16:48:10.826643 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000501945 (* 0.0454545 = 2.28157e-05 loss) | |
| I0407 16:48:10.826655 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:48:10.826668 1004 solver.cpp:245] Train net output #45: total_confidence = 7.57177e-05 | |
| I0407 16:48:10.826680 1004 sgd_solver.cpp:106] Iteration 71000, lr = 0.000858 | |
| I0407 16:48:50.238384 1004 solver.cpp:229] Iteration 71500, loss = 0.979026 | |
| I0407 16:48:50.238504 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.25 | |
| I0407 16:48:50.238524 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:48:50.238538 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:48:50.238550 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.25 | |
| I0407 16:48:50.238562 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.3125 | |
| I0407 16:48:50.238575 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 16:48:50.238587 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 16:48:50.238600 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:48:50.238610 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:48:50.238622 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:48:50.238634 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:48:50.238646 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:48:50.238656 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:48:50.238668 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:48:50.238679 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:48:50.238692 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:48:50.238703 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:48:50.238713 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:48:50.238725 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:48:50.238736 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:48:50.238747 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:48:50.238759 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:48:50.238775 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.07358 (* 0.0454545 = 0.139708 loss) | |
| I0407 16:48:50.238790 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.48504 (* 0.0454545 = 0.158411 loss) | |
| I0407 16:48:50.238802 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.52541 (* 0.0454545 = 0.160246 loss) | |
| I0407 16:48:50.238816 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.41413 (* 0.0454545 = 0.155188 loss) | |
| I0407 16:48:50.238831 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.01739 (* 0.0454545 = 0.137154 loss) | |
| I0407 16:48:50.238844 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.60458 (* 0.0454545 = 0.11839 loss) | |
| I0407 16:48:50.238857 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.29621 (* 0.0454545 = 0.0589185 loss) | |
| I0407 16:48:50.238872 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.357785 (* 0.0454545 = 0.0162629 loss) | |
| I0407 16:48:50.238885 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.324984 (* 0.0454545 = 0.014772 loss) | |
| I0407 16:48:50.238899 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0168442 (* 0.0454545 = 0.000765647 loss) | |
| I0407 16:48:50.238914 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000170972 (* 0.0454545 = 7.77144e-06 loss) | |
| I0407 16:48:50.238931 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000176552 (* 0.0454545 = 8.02508e-06 loss) | |
| I0407 16:48:50.238945 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000150282 (* 0.0454545 = 6.83098e-06 loss) | |
| I0407 16:48:50.238960 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000156381 (* 0.0454545 = 7.10821e-06 loss) | |
| I0407 16:48:50.238973 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000157039 (* 0.0454545 = 7.13813e-06 loss) | |
| I0407 16:48:50.238987 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000144512 (* 0.0454545 = 6.56873e-06 loss) | |
| I0407 16:48:50.239002 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000156181 (* 0.0454545 = 7.09913e-06 loss) | |
| I0407 16:48:50.239033 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000149532 (* 0.0454545 = 6.7969e-06 loss) | |
| I0407 16:48:50.239048 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000153139 (* 0.0454545 = 6.96086e-06 loss) | |
| I0407 16:48:50.239063 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000151169 (* 0.0454545 = 6.87133e-06 loss) | |
| I0407 16:48:50.239076 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000140532 (* 0.0454545 = 6.38781e-06 loss) | |
| I0407 16:48:50.239090 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000152275 (* 0.0454545 = 6.92159e-06 loss) | |
| I0407 16:48:50.239102 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:48:50.239114 1004 solver.cpp:245] Train net output #45: total_confidence = 9.18186e-05 | |
| I0407 16:48:50.239127 1004 sgd_solver.cpp:106] Iteration 71500, lr = 0.000857 | |
| I0407 16:49:29.120764 1004 solver.cpp:229] Iteration 72000, loss = 0.980921 | |
| I0407 16:49:29.120896 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:49:29.120915 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:49:29.120931 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:49:29.120944 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 16:49:29.120956 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 16:49:29.120968 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.25 | |
| I0407 16:49:29.120980 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 16:49:29.120991 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.75 | |
| I0407 16:49:29.121003 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:49:29.121016 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:49:29.121026 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:49:29.121038 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:49:29.121049 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:49:29.121062 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:49:29.121073 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:49:29.121084 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:49:29.121095 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:49:29.121106 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:49:29.121119 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:49:29.121130 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:49:29.121141 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:49:29.121153 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:49:29.121168 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.23398 (* 0.0454545 = 0.146999 loss) | |
| I0407 16:49:29.121183 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.70162 (* 0.0454545 = 0.168255 loss) | |
| I0407 16:49:29.121197 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.35333 (* 0.0454545 = 0.152424 loss) | |
| I0407 16:49:29.121212 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.65973 (* 0.0454545 = 0.166351 loss) | |
| I0407 16:49:29.121224 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.05036 (* 0.0454545 = 0.138653 loss) | |
| I0407 16:49:29.121239 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.82331 (* 0.0454545 = 0.128332 loss) | |
| I0407 16:49:29.121253 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.20128 (* 0.0454545 = 0.0546037 loss) | |
| I0407 16:49:29.121266 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.18057 (* 0.0454545 = 0.0536623 loss) | |
| I0407 16:49:29.121280 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0609495 (* 0.0454545 = 0.00277043 loss) | |
| I0407 16:49:29.121294 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0220405 (* 0.0454545 = 0.00100184 loss) | |
| I0407 16:49:29.121309 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000248922 (* 0.0454545 = 1.13147e-05 loss) | |
| I0407 16:49:29.121322 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000216684 (* 0.0454545 = 9.8493e-06 loss) | |
| I0407 16:49:29.121337 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000218962 (* 0.0454545 = 9.95283e-06 loss) | |
| I0407 16:49:29.121351 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000257867 (* 0.0454545 = 1.17212e-05 loss) | |
| I0407 16:49:29.121366 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000206989 (* 0.0454545 = 9.40857e-06 loss) | |
| I0407 16:49:29.121379 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000193074 (* 0.0454545 = 8.77609e-06 loss) | |
| I0407 16:49:29.121393 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000232728 (* 0.0454545 = 1.05785e-05 loss) | |
| I0407 16:49:29.121424 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000227041 (* 0.0454545 = 1.032e-05 loss) | |
| I0407 16:49:29.121440 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000213602 (* 0.0454545 = 9.7092e-06 loss) | |
| I0407 16:49:29.121454 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000200485 (* 0.0454545 = 9.11295e-06 loss) | |
| I0407 16:49:29.121469 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000218741 (* 0.0454545 = 9.94278e-06 loss) | |
| I0407 16:49:29.121482 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000197279 (* 0.0454545 = 8.96725e-06 loss) | |
| I0407 16:49:29.121495 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:49:29.121506 1004 solver.cpp:245] Train net output #45: total_confidence = 8.21621e-06 | |
| I0407 16:49:29.121520 1004 sgd_solver.cpp:106] Iteration 72000, lr = 0.000856 | |
| I0407 16:50:08.040314 1004 solver.cpp:229] Iteration 72500, loss = 0.979003 | |
| I0407 16:50:08.040472 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.1875 | |
| I0407 16:50:08.040503 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:50:08.040529 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:50:08.040544 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.25 | |
| I0407 16:50:08.040557 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.4375 | |
| I0407 16:50:08.040570 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5625 | |
| I0407 16:50:08.040581 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 16:50:08.040593 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 16:50:08.040606 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:50:08.040616 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:50:08.040628 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:50:08.040639 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:50:08.040652 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:50:08.040663 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:50:08.040673 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:50:08.040684 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:50:08.040696 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:50:08.040707 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:50:08.040719 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:50:08.040730 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:50:08.040741 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:50:08.040753 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:50:08.040768 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.08177 (* 0.0454545 = 0.140081 loss) | |
| I0407 16:50:08.040783 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.30651 (* 0.0454545 = 0.150296 loss) | |
| I0407 16:50:08.040797 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.4273 (* 0.0454545 = 0.155786 loss) | |
| I0407 16:50:08.040812 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.10579 (* 0.0454545 = 0.141172 loss) | |
| I0407 16:50:08.040825 1004 solver.cpp:245] Train net output #26: loss/loss05 = 2.41054 (* 0.0454545 = 0.10957 loss) | |
| I0407 16:50:08.040839 1004 solver.cpp:245] Train net output #27: loss/loss06 = 1.88966 (* 0.0454545 = 0.0858938 loss) | |
| I0407 16:50:08.040853 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.16186 (* 0.0454545 = 0.052812 loss) | |
| I0407 16:50:08.040868 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.664698 (* 0.0454545 = 0.0302135 loss) | |
| I0407 16:50:08.040881 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0421667 (* 0.0454545 = 0.00191667 loss) | |
| I0407 16:50:08.040895 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0140516 (* 0.0454545 = 0.00063871 loss) | |
| I0407 16:50:08.040910 1004 solver.cpp:245] Train net output #32: loss/loss11 = 1.05728e-05 (* 0.0454545 = 4.80582e-07 loss) | |
| I0407 16:50:08.040927 1004 solver.cpp:245] Train net output #33: loss/loss12 = 9.64884e-06 (* 0.0454545 = 4.38584e-07 loss) | |
| I0407 16:50:08.040942 1004 solver.cpp:245] Train net output #34: loss/loss13 = 8.8516e-06 (* 0.0454545 = 4.02346e-07 loss) | |
| I0407 16:50:08.040956 1004 solver.cpp:245] Train net output #35: loss/loss14 = 8.38218e-06 (* 0.0454545 = 3.81008e-07 loss) | |
| I0407 16:50:08.040971 1004 solver.cpp:245] Train net output #36: loss/loss15 = 7.39864e-06 (* 0.0454545 = 3.36302e-07 loss) | |
| I0407 16:50:08.040984 1004 solver.cpp:245] Train net output #37: loss/loss16 = 7.06333e-06 (* 0.0454545 = 3.21061e-07 loss) | |
| I0407 16:50:08.040998 1004 solver.cpp:245] Train net output #38: loss/loss17 = 7.84569e-06 (* 0.0454545 = 3.56622e-07 loss) | |
| I0407 16:50:08.041026 1004 solver.cpp:245] Train net output #39: loss/loss18 = 7.33158e-06 (* 0.0454545 = 3.33253e-07 loss) | |
| I0407 16:50:08.041043 1004 solver.cpp:245] Train net output #40: loss/loss19 = 7.17509e-06 (* 0.0454545 = 3.26141e-07 loss) | |
| I0407 16:50:08.041056 1004 solver.cpp:245] Train net output #41: loss/loss20 = 6.75039e-06 (* 0.0454545 = 3.06836e-07 loss) | |
| I0407 16:50:08.041070 1004 solver.cpp:245] Train net output #42: loss/loss21 = 6.04254e-06 (* 0.0454545 = 2.74661e-07 loss) | |
| I0407 16:50:08.041085 1004 solver.cpp:245] Train net output #43: loss/loss22 = 7.56256e-06 (* 0.0454545 = 3.43753e-07 loss) | |
| I0407 16:50:08.041096 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:50:08.041107 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000355686 | |
| I0407 16:50:08.041121 1004 sgd_solver.cpp:106] Iteration 72500, lr = 0.000855 | |
| I0407 16:50:46.850499 1004 solver.cpp:229] Iteration 73000, loss = 0.977415 | |
| I0407 16:50:46.850635 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:50:46.850654 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:50:46.850667 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 16:50:46.850679 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 16:50:46.850692 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 16:50:46.850704 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.1875 | |
| I0407 16:50:46.850716 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.5625 | |
| I0407 16:50:46.850728 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:50:46.850740 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:50:46.850752 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 16:50:46.850764 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:50:46.850775 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:50:46.850787 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:50:46.850798 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:50:46.850810 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:50:46.850821 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:50:46.850832 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:50:46.850844 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:50:46.850855 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:50:46.850867 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:50:46.850878 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:50:46.850889 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:50:46.850905 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.29575 (* 0.0454545 = 0.149807 loss) | |
| I0407 16:50:46.850922 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.52597 (* 0.0454545 = 0.160271 loss) | |
| I0407 16:50:46.850936 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.65502 (* 0.0454545 = 0.166137 loss) | |
| I0407 16:50:46.850950 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.47927 (* 0.0454545 = 0.158149 loss) | |
| I0407 16:50:46.850965 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.5341 (* 0.0454545 = 0.160641 loss) | |
| I0407 16:50:46.850978 1004 solver.cpp:245] Train net output #27: loss/loss06 = 3.30494 (* 0.0454545 = 0.150224 loss) | |
| I0407 16:50:46.850992 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.95541 (* 0.0454545 = 0.0888825 loss) | |
| I0407 16:50:46.851006 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.394707 (* 0.0454545 = 0.0179412 loss) | |
| I0407 16:50:46.851019 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.347627 (* 0.0454545 = 0.0158012 loss) | |
| I0407 16:50:46.851033 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.378202 (* 0.0454545 = 0.017191 loss) | |
| I0407 16:50:46.851047 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000640229 (* 0.0454545 = 2.91013e-05 loss) | |
| I0407 16:50:46.851063 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000656042 (* 0.0454545 = 2.98201e-05 loss) | |
| I0407 16:50:46.851076 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000610506 (* 0.0454545 = 2.77503e-05 loss) | |
| I0407 16:50:46.851090 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000618314 (* 0.0454545 = 2.81052e-05 loss) | |
| I0407 16:50:46.851104 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000642292 (* 0.0454545 = 2.91951e-05 loss) | |
| I0407 16:50:46.851119 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000571178 (* 0.0454545 = 2.59626e-05 loss) | |
| I0407 16:50:46.851132 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000630771 (* 0.0454545 = 2.86714e-05 loss) | |
| I0407 16:50:46.851164 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000605655 (* 0.0454545 = 2.75298e-05 loss) | |
| I0407 16:50:46.851179 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000594065 (* 0.0454545 = 2.7003e-05 loss) | |
| I0407 16:50:46.851193 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000621346 (* 0.0454545 = 2.8243e-05 loss) | |
| I0407 16:50:46.851208 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000590971 (* 0.0454545 = 2.68623e-05 loss) | |
| I0407 16:50:46.851222 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000573608 (* 0.0454545 = 2.60731e-05 loss) | |
| I0407 16:50:46.851234 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:50:46.851245 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000204375 | |
| I0407 16:50:46.851258 1004 sgd_solver.cpp:106] Iteration 73000, lr = 0.000854 | |
| I0407 16:51:26.333524 1004 solver.cpp:229] Iteration 73500, loss = 0.975353 | |
| I0407 16:51:26.333660 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:51:26.333680 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:51:26.333693 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:51:26.333706 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.25 | |
| I0407 16:51:26.333719 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.4375 | |
| I0407 16:51:26.333730 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 16:51:26.333742 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 16:51:26.333753 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:51:26.333765 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:51:26.333777 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:51:26.333789 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:51:26.333801 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:51:26.333812 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:51:26.333823 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:51:26.333834 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:51:26.333847 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:51:26.333858 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:51:26.333869 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:51:26.333880 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:51:26.333892 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:51:26.333904 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:51:26.333915 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:51:26.333935 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.14345 (* 0.0454545 = 0.142884 loss) | |
| I0407 16:51:26.333950 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.36889 (* 0.0454545 = 0.153131 loss) | |
| I0407 16:51:26.333963 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.49515 (* 0.0454545 = 0.15887 loss) | |
| I0407 16:51:26.333977 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.18248 (* 0.0454545 = 0.144658 loss) | |
| I0407 16:51:26.333992 1004 solver.cpp:245] Train net output #26: loss/loss05 = 2.53947 (* 0.0454545 = 0.11543 loss) | |
| I0407 16:51:26.334004 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.74262 (* 0.0454545 = 0.124665 loss) | |
| I0407 16:51:26.334018 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.32509 (* 0.0454545 = 0.0602315 loss) | |
| I0407 16:51:26.334033 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.211571 (* 0.0454545 = 0.00961685 loss) | |
| I0407 16:51:26.334048 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0314857 (* 0.0454545 = 0.00143117 loss) | |
| I0407 16:51:26.334063 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0106502 (* 0.0454545 = 0.000484102 loss) | |
| I0407 16:51:26.334077 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000418161 (* 0.0454545 = 1.90073e-05 loss) | |
| I0407 16:51:26.334091 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00037176 (* 0.0454545 = 1.68982e-05 loss) | |
| I0407 16:51:26.334105 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.00039388 (* 0.0454545 = 1.79037e-05 loss) | |
| I0407 16:51:26.334120 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000416196 (* 0.0454545 = 1.8918e-05 loss) | |
| I0407 16:51:26.334134 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000382772 (* 0.0454545 = 1.73987e-05 loss) | |
| I0407 16:51:26.334148 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000357884 (* 0.0454545 = 1.62675e-05 loss) | |
| I0407 16:51:26.334162 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000412095 (* 0.0454545 = 1.87316e-05 loss) | |
| I0407 16:51:26.334194 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000399154 (* 0.0454545 = 1.81434e-05 loss) | |
| I0407 16:51:26.334209 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000362052 (* 0.0454545 = 1.64569e-05 loss) | |
| I0407 16:51:26.334224 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000377155 (* 0.0454545 = 1.71434e-05 loss) | |
| I0407 16:51:26.334239 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000367789 (* 0.0454545 = 1.67177e-05 loss) | |
| I0407 16:51:26.334252 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000406274 (* 0.0454545 = 1.8467e-05 loss) | |
| I0407 16:51:26.334264 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:51:26.334275 1004 solver.cpp:245] Train net output #45: total_confidence = 0.00146487 | |
| I0407 16:51:26.334290 1004 sgd_solver.cpp:106] Iteration 73500, lr = 0.000853 | |
| I0407 16:52:04.834365 1004 solver.cpp:229] Iteration 74000, loss = 0.976655 | |
| I0407 16:52:04.834465 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:52:04.834483 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:52:04.834496 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:52:04.834508 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 16:52:04.834520 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 16:52:04.834533 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.25 | |
| I0407 16:52:04.834544 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.625 | |
| I0407 16:52:04.834556 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 16:52:04.834568 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:52:04.834580 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 16:52:04.834592 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:52:04.834604 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:52:04.834615 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:52:04.834626 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:52:04.834637 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:52:04.834650 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:52:04.834661 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:52:04.834671 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:52:04.834683 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:52:04.834694 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:52:04.834715 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:52:04.834736 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:52:04.834754 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.05635 (* 0.0454545 = 0.138925 loss) | |
| I0407 16:52:04.834769 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.57087 (* 0.0454545 = 0.162312 loss) | |
| I0407 16:52:04.834782 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.34507 (* 0.0454545 = 0.152049 loss) | |
| I0407 16:52:04.834796 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.67077 (* 0.0454545 = 0.166853 loss) | |
| I0407 16:52:04.834810 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.43539 (* 0.0454545 = 0.156154 loss) | |
| I0407 16:52:04.834825 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.95876 (* 0.0454545 = 0.134489 loss) | |
| I0407 16:52:04.834838 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.87827 (* 0.0454545 = 0.0853757 loss) | |
| I0407 16:52:04.834852 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.591076 (* 0.0454545 = 0.0268671 loss) | |
| I0407 16:52:04.834867 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.282283 (* 0.0454545 = 0.0128311 loss) | |
| I0407 16:52:04.834880 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.243317 (* 0.0454545 = 0.0110599 loss) | |
| I0407 16:52:04.834894 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000287014 (* 0.0454545 = 1.30461e-05 loss) | |
| I0407 16:52:04.834908 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000262509 (* 0.0454545 = 1.19322e-05 loss) | |
| I0407 16:52:04.834923 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000246069 (* 0.0454545 = 1.11849e-05 loss) | |
| I0407 16:52:04.834936 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000249224 (* 0.0454545 = 1.13284e-05 loss) | |
| I0407 16:52:04.834950 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000264406 (* 0.0454545 = 1.20185e-05 loss) | |
| I0407 16:52:04.834964 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.00023236 (* 0.0454545 = 1.05618e-05 loss) | |
| I0407 16:52:04.834978 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000256271 (* 0.0454545 = 1.16487e-05 loss) | |
| I0407 16:52:04.835010 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000266894 (* 0.0454545 = 1.21316e-05 loss) | |
| I0407 16:52:04.835026 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000220207 (* 0.0454545 = 1.00094e-05 loss) | |
| I0407 16:52:04.835039 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000212381 (* 0.0454545 = 9.65369e-06 loss) | |
| I0407 16:52:04.835053 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000265216 (* 0.0454545 = 1.20553e-05 loss) | |
| I0407 16:52:04.835067 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000248472 (* 0.0454545 = 1.12942e-05 loss) | |
| I0407 16:52:04.835083 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:52:04.835094 1004 solver.cpp:245] Train net output #45: total_confidence = 2.21439e-05 | |
| I0407 16:52:04.835108 1004 sgd_solver.cpp:106] Iteration 74000, lr = 0.000852 | |
| I0407 16:52:44.547813 1004 solver.cpp:229] Iteration 74500, loss = 0.97858 | |
| I0407 16:52:44.547962 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:52:44.547982 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:52:44.547996 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:52:44.548008 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 16:52:44.548020 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 16:52:44.548033 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 16:52:44.548045 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 16:52:44.548058 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:52:44.548069 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:52:44.548081 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:52:44.548092 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:52:44.548105 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:52:44.548115 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:52:44.548127 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:52:44.548140 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:52:44.548151 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:52:44.548162 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:52:44.548173 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:52:44.548185 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:52:44.548197 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:52:44.548208 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:52:44.548219 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:52:44.548234 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.18874 (* 0.0454545 = 0.144943 loss) | |
| I0407 16:52:44.548249 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.33845 (* 0.0454545 = 0.151748 loss) | |
| I0407 16:52:44.548264 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.3458 (* 0.0454545 = 0.152082 loss) | |
| I0407 16:52:44.548277 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.1212 (* 0.0454545 = 0.141873 loss) | |
| I0407 16:52:44.548291 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.0424 (* 0.0454545 = 0.138291 loss) | |
| I0407 16:52:44.548305 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.57447 (* 0.0454545 = 0.117022 loss) | |
| I0407 16:52:44.548319 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.985628 (* 0.0454545 = 0.0448013 loss) | |
| I0407 16:52:44.548332 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.414793 (* 0.0454545 = 0.0188542 loss) | |
| I0407 16:52:44.548347 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0070902 (* 0.0454545 = 0.000322282 loss) | |
| I0407 16:52:44.548362 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.00265788 (* 0.0454545 = 0.000120813 loss) | |
| I0407 16:52:44.548375 1004 solver.cpp:245] Train net output #32: loss/loss11 = 2.4802e-05 (* 0.0454545 = 1.12736e-06 loss) | |
| I0407 16:52:44.548390 1004 solver.cpp:245] Train net output #33: loss/loss12 = 2.50554e-05 (* 0.0454545 = 1.13888e-06 loss) | |
| I0407 16:52:44.548404 1004 solver.cpp:245] Train net output #34: loss/loss13 = 2.17542e-05 (* 0.0454545 = 9.88825e-07 loss) | |
| I0407 16:52:44.548419 1004 solver.cpp:245] Train net output #35: loss/loss14 = 2.36919e-05 (* 0.0454545 = 1.0769e-06 loss) | |
| I0407 16:52:44.548434 1004 solver.cpp:245] Train net output #36: loss/loss15 = 2.3908e-05 (* 0.0454545 = 1.08673e-06 loss) | |
| I0407 16:52:44.548447 1004 solver.cpp:245] Train net output #37: loss/loss16 = 2.36696e-05 (* 0.0454545 = 1.07589e-06 loss) | |
| I0407 16:52:44.548461 1004 solver.cpp:245] Train net output #38: loss/loss17 = 2.69898e-05 (* 0.0454545 = 1.22681e-06 loss) | |
| I0407 16:52:44.548488 1004 solver.cpp:245] Train net output #39: loss/loss18 = 2.60654e-05 (* 0.0454545 = 1.18479e-06 loss) | |
| I0407 16:52:44.548503 1004 solver.cpp:245] Train net output #40: loss/loss19 = 2.1404e-05 (* 0.0454545 = 9.72909e-07 loss) | |
| I0407 16:52:44.548518 1004 solver.cpp:245] Train net output #41: loss/loss20 = 2.29243e-05 (* 0.0454545 = 1.04202e-06 loss) | |
| I0407 16:52:44.548532 1004 solver.cpp:245] Train net output #42: loss/loss21 = 2.41614e-05 (* 0.0454545 = 1.09825e-06 loss) | |
| I0407 16:52:44.548547 1004 solver.cpp:245] Train net output #43: loss/loss22 = 2.47614e-05 (* 0.0454545 = 1.12552e-06 loss) | |
| I0407 16:52:44.548558 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:52:44.548570 1004 solver.cpp:245] Train net output #45: total_confidence = 7.98787e-05 | |
| I0407 16:52:44.548583 1004 sgd_solver.cpp:106] Iteration 74500, lr = 0.000851 | |
| I0407 16:53:23.274535 1004 solver.cpp:338] Iteration 75000, Testing net (#0) | |
| I0407 16:53:31.209463 1004 solver.cpp:393] Test loss: 0.885413 | |
| I0407 16:53:31.209514 1004 solver.cpp:406] Test net output #0: loss/accuracy01 = 0.329 | |
| I0407 16:53:31.209532 1004 solver.cpp:406] Test net output #1: loss/accuracy02 = 0.088 | |
| I0407 16:53:31.209544 1004 solver.cpp:406] Test net output #2: loss/accuracy03 = 0.085 | |
| I0407 16:53:31.209558 1004 solver.cpp:406] Test net output #3: loss/accuracy04 = 0.082 | |
| I0407 16:53:31.209569 1004 solver.cpp:406] Test net output #4: loss/accuracy05 = 0.203 | |
| I0407 16:53:31.209580 1004 solver.cpp:406] Test net output #5: loss/accuracy06 = 0.495 | |
| I0407 16:53:31.209592 1004 solver.cpp:406] Test net output #6: loss/accuracy07 = 0.894 | |
| I0407 16:53:31.209604 1004 solver.cpp:406] Test net output #7: loss/accuracy08 = 0.97 | |
| I0407 16:53:31.209614 1004 solver.cpp:406] Test net output #8: loss/accuracy09 = 0.995 | |
| I0407 16:53:31.209625 1004 solver.cpp:406] Test net output #9: loss/accuracy10 = 0.998 | |
| I0407 16:53:31.209637 1004 solver.cpp:406] Test net output #10: loss/accuracy11 = 1 | |
| I0407 16:53:31.209650 1004 solver.cpp:406] Test net output #11: loss/accuracy12 = 1 | |
| I0407 16:53:31.209661 1004 solver.cpp:406] Test net output #12: loss/accuracy13 = 1 | |
| I0407 16:53:31.209671 1004 solver.cpp:406] Test net output #13: loss/accuracy14 = 1 | |
| I0407 16:53:31.209682 1004 solver.cpp:406] Test net output #14: loss/accuracy15 = 1 | |
| I0407 16:53:31.209693 1004 solver.cpp:406] Test net output #15: loss/accuracy16 = 1 | |
| I0407 16:53:31.209704 1004 solver.cpp:406] Test net output #16: loss/accuracy17 = 1 | |
| I0407 16:53:31.209715 1004 solver.cpp:406] Test net output #17: loss/accuracy18 = 1 | |
| I0407 16:53:31.209727 1004 solver.cpp:406] Test net output #18: loss/accuracy19 = 1 | |
| I0407 16:53:31.209738 1004 solver.cpp:406] Test net output #19: loss/accuracy20 = 1 | |
| I0407 16:53:31.209748 1004 solver.cpp:406] Test net output #20: loss/accuracy21 = 1 | |
| I0407 16:53:31.209759 1004 solver.cpp:406] Test net output #21: loss/accuracy22 = 1 | |
| I0407 16:53:31.209774 1004 solver.cpp:406] Test net output #22: loss/loss01 = 3.08337 (* 0.0454545 = 0.140153 loss) | |
| I0407 16:53:31.209789 1004 solver.cpp:406] Test net output #23: loss/loss02 = 3.21283 (* 0.0454545 = 0.146038 loss) | |
| I0407 16:53:31.209802 1004 solver.cpp:406] Test net output #24: loss/loss03 = 3.31481 (* 0.0454545 = 0.150673 loss) | |
| I0407 16:53:31.209815 1004 solver.cpp:406] Test net output #25: loss/loss04 = 3.27663 (* 0.0454545 = 0.148938 loss) | |
| I0407 16:53:31.209828 1004 solver.cpp:406] Test net output #26: loss/loss05 = 3.22167 (* 0.0454545 = 0.146439 loss) | |
| I0407 16:53:31.209842 1004 solver.cpp:406] Test net output #27: loss/loss06 = 2.27051 (* 0.0454545 = 0.103205 loss) | |
| I0407 16:53:31.209856 1004 solver.cpp:406] Test net output #28: loss/loss07 = 0.748306 (* 0.0454545 = 0.0340139 loss) | |
| I0407 16:53:31.209868 1004 solver.cpp:406] Test net output #29: loss/loss08 = 0.260556 (* 0.0454545 = 0.0118435 loss) | |
| I0407 16:53:31.209882 1004 solver.cpp:406] Test net output #30: loss/loss09 = 0.0571233 (* 0.0454545 = 0.00259651 loss) | |
| I0407 16:53:31.209897 1004 solver.cpp:406] Test net output #31: loss/loss10 = 0.0290581 (* 0.0454545 = 0.00132082 loss) | |
| I0407 16:53:31.209910 1004 solver.cpp:406] Test net output #32: loss/loss11 = 0.000375904 (* 0.0454545 = 1.70866e-05 loss) | |
| I0407 16:53:31.209928 1004 solver.cpp:406] Test net output #33: loss/loss12 = 0.000349961 (* 0.0454545 = 1.59073e-05 loss) | |
| I0407 16:53:31.209944 1004 solver.cpp:406] Test net output #34: loss/loss13 = 0.000341537 (* 0.0454545 = 1.55244e-05 loss) | |
| I0407 16:53:31.209957 1004 solver.cpp:406] Test net output #35: loss/loss14 = 0.00034331 (* 0.0454545 = 1.5605e-05 loss) | |
| I0407 16:53:31.209971 1004 solver.cpp:406] Test net output #36: loss/loss15 = 0.000360485 (* 0.0454545 = 1.63857e-05 loss) | |
| I0407 16:53:31.209985 1004 solver.cpp:406] Test net output #37: loss/loss16 = 0.000336212 (* 0.0454545 = 1.52823e-05 loss) | |
| I0407 16:53:31.210000 1004 solver.cpp:406] Test net output #38: loss/loss17 = 0.000368655 (* 0.0454545 = 1.67571e-05 loss) | |
| I0407 16:53:31.210047 1004 solver.cpp:406] Test net output #39: loss/loss18 = 0.00037816 (* 0.0454545 = 1.71891e-05 loss) | |
| I0407 16:53:31.210063 1004 solver.cpp:406] Test net output #40: loss/loss19 = 0.000341486 (* 0.0454545 = 1.55221e-05 loss) | |
| I0407 16:53:31.210078 1004 solver.cpp:406] Test net output #41: loss/loss20 = 0.000324088 (* 0.0454545 = 1.47313e-05 loss) | |
| I0407 16:53:31.210091 1004 solver.cpp:406] Test net output #42: loss/loss21 = 0.000358154 (* 0.0454545 = 1.62797e-05 loss) | |
| I0407 16:53:31.210105 1004 solver.cpp:406] Test net output #43: loss/loss22 = 0.000347836 (* 0.0454545 = 1.58107e-05 loss) | |
| I0407 16:53:31.210116 1004 solver.cpp:406] Test net output #44: total_accuracy = 0.001 | |
| I0407 16:53:31.210129 1004 solver.cpp:406] Test net output #45: total_confidence = 0.000255982 | |
| I0407 16:53:31.232305 1004 solver.cpp:229] Iteration 75000, loss = 0.98021 | |
| I0407 16:53:31.232341 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:53:31.232357 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 16:53:31.232370 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:53:31.232383 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 16:53:31.232393 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.3125 | |
| I0407 16:53:31.232405 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5625 | |
| I0407 16:53:31.232417 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.9375 | |
| I0407 16:53:31.232429 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 16:53:31.232440 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:53:31.232451 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:53:31.232462 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:53:31.232473 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:53:31.232486 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:53:31.232496 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:53:31.232507 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:53:31.232518 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:53:31.232530 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:53:31.232542 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:53:31.232553 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:53:31.232563 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:53:31.232574 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:53:31.232586 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:53:31.232600 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.08853 (* 0.0454545 = 0.140388 loss) | |
| I0407 16:53:31.232614 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.27711 (* 0.0454545 = 0.14896 loss) | |
| I0407 16:53:31.232628 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.29342 (* 0.0454545 = 0.149701 loss) | |
| I0407 16:53:31.232642 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.02435 (* 0.0454545 = 0.13747 loss) | |
| I0407 16:53:31.232656 1004 solver.cpp:245] Train net output #26: loss/loss05 = 2.76472 (* 0.0454545 = 0.125669 loss) | |
| I0407 16:53:31.232669 1004 solver.cpp:245] Train net output #27: loss/loss06 = 1.96764 (* 0.0454545 = 0.0894381 loss) | |
| I0407 16:53:31.232682 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.51109 (* 0.0454545 = 0.0232314 loss) | |
| I0407 16:53:31.232697 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.102002 (* 0.0454545 = 0.00463645 loss) | |
| I0407 16:53:31.232712 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0260088 (* 0.0454545 = 0.00118222 loss) | |
| I0407 16:53:31.232725 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0107043 (* 0.0454545 = 0.000486561 loss) | |
| I0407 16:53:31.232756 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000428893 (* 0.0454545 = 1.94952e-05 loss) | |
| I0407 16:53:31.232772 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000417747 (* 0.0454545 = 1.89885e-05 loss) | |
| I0407 16:53:31.232786 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000459744 (* 0.0454545 = 2.08975e-05 loss) | |
| I0407 16:53:31.232800 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000406428 (* 0.0454545 = 1.8474e-05 loss) | |
| I0407 16:53:31.232815 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000424122 (* 0.0454545 = 1.92783e-05 loss) | |
| I0407 16:53:31.232830 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000454203 (* 0.0454545 = 2.06456e-05 loss) | |
| I0407 16:53:31.232842 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000421065 (* 0.0454545 = 1.91393e-05 loss) | |
| I0407 16:53:31.232856 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000515466 (* 0.0454545 = 2.34303e-05 loss) | |
| I0407 16:53:31.232870 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000465245 (* 0.0454545 = 2.11475e-05 loss) | |
| I0407 16:53:31.232884 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000403694 (* 0.0454545 = 1.83497e-05 loss) | |
| I0407 16:53:31.232899 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.00047205 (* 0.0454545 = 2.14568e-05 loss) | |
| I0407 16:53:31.232913 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000424602 (* 0.0454545 = 1.93001e-05 loss) | |
| I0407 16:53:31.232924 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:53:31.232936 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000557626 | |
| I0407 16:53:31.232950 1004 sgd_solver.cpp:106] Iteration 75000, lr = 0.00085 | |
| I0407 16:54:09.479434 1004 solver.cpp:229] Iteration 75500, loss = 0.972105 | |
| I0407 16:54:09.479544 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.1875 | |
| I0407 16:54:09.479563 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:54:09.479576 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:54:09.479589 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 16:54:09.479601 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 16:54:09.479614 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 16:54:09.479624 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 16:54:09.479636 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.75 | |
| I0407 16:54:09.479647 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.875 | |
| I0407 16:54:09.479660 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.875 | |
| I0407 16:54:09.479671 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:54:09.479683 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:54:09.479694 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:54:09.479707 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:54:09.479717 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:54:09.479728 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:54:09.479740 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:54:09.479751 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:54:09.479763 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:54:09.479774 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:54:09.479786 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:54:09.479797 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:54:09.479812 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.37642 (* 0.0454545 = 0.153473 loss) | |
| I0407 16:54:09.479827 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.88795 (* 0.0454545 = 0.176725 loss) | |
| I0407 16:54:09.479841 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.42294 (* 0.0454545 = 0.155588 loss) | |
| I0407 16:54:09.479854 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.28083 (* 0.0454545 = 0.149129 loss) | |
| I0407 16:54:09.479868 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.4706 (* 0.0454545 = 0.157755 loss) | |
| I0407 16:54:09.479882 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.56336 (* 0.0454545 = 0.116516 loss) | |
| I0407 16:54:09.479897 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.15026 (* 0.0454545 = 0.0522847 loss) | |
| I0407 16:54:09.479909 1004 solver.cpp:245] Train net output #29: loss/loss08 = 1.01686 (* 0.0454545 = 0.046221 loss) | |
| I0407 16:54:09.479926 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.65901 (* 0.0454545 = 0.029955 loss) | |
| I0407 16:54:09.479940 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.651094 (* 0.0454545 = 0.0295952 loss) | |
| I0407 16:54:09.479955 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000228092 (* 0.0454545 = 1.03678e-05 loss) | |
| I0407 16:54:09.479969 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000211699 (* 0.0454545 = 9.62268e-06 loss) | |
| I0407 16:54:09.479984 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000199935 (* 0.0454545 = 9.08794e-06 loss) | |
| I0407 16:54:09.479997 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000198611 (* 0.0454545 = 9.02777e-06 loss) | |
| I0407 16:54:09.480012 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000227214 (* 0.0454545 = 1.03279e-05 loss) | |
| I0407 16:54:09.480026 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000214487 (* 0.0454545 = 9.74941e-06 loss) | |
| I0407 16:54:09.480041 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000244646 (* 0.0454545 = 1.11203e-05 loss) | |
| I0407 16:54:09.480072 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000238709 (* 0.0454545 = 1.08504e-05 loss) | |
| I0407 16:54:09.480087 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.00020072 (* 0.0454545 = 9.12364e-06 loss) | |
| I0407 16:54:09.480100 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.00017853 (* 0.0454545 = 8.11499e-06 loss) | |
| I0407 16:54:09.480114 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000222656 (* 0.0454545 = 1.01207e-05 loss) | |
| I0407 16:54:09.480129 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000207757 (* 0.0454545 = 9.44351e-06 loss) | |
| I0407 16:54:09.480139 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:54:09.480151 1004 solver.cpp:245] Train net output #45: total_confidence = 8.13313e-06 | |
| I0407 16:54:09.480165 1004 sgd_solver.cpp:106] Iteration 75500, lr = 0.000849 | |
| I0407 16:54:48.156548 1004 solver.cpp:229] Iteration 76000, loss = 0.974559 | |
| I0407 16:54:48.156827 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:54:48.156848 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:54:48.156862 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.1875 | |
| I0407 16:54:48.156873 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 16:54:48.156885 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 16:54:48.156898 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 16:54:48.156909 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 16:54:48.156924 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 16:54:48.156937 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:54:48.156949 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:54:48.156960 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:54:48.156972 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:54:48.156983 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:54:48.156996 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:54:48.157007 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:54:48.157018 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:54:48.157032 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:54:48.157042 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:54:48.157054 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:54:48.157065 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:54:48.157076 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:54:48.157088 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:54:48.157104 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.08221 (* 0.0454545 = 0.140101 loss) | |
| I0407 16:54:48.157117 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.26759 (* 0.0454545 = 0.148527 loss) | |
| I0407 16:54:48.157131 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.17508 (* 0.0454545 = 0.144322 loss) | |
| I0407 16:54:48.157145 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.32818 (* 0.0454545 = 0.151281 loss) | |
| I0407 16:54:48.157158 1004 solver.cpp:245] Train net output #26: loss/loss05 = 2.92578 (* 0.0454545 = 0.13299 loss) | |
| I0407 16:54:48.157172 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.4466 (* 0.0454545 = 0.111209 loss) | |
| I0407 16:54:48.157186 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.877623 (* 0.0454545 = 0.039892 loss) | |
| I0407 16:54:48.157201 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.894213 (* 0.0454545 = 0.040646 loss) | |
| I0407 16:54:48.157214 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.384649 (* 0.0454545 = 0.0174841 loss) | |
| I0407 16:54:48.157228 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.00855819 (* 0.0454545 = 0.000389009 loss) | |
| I0407 16:54:48.157243 1004 solver.cpp:245] Train net output #32: loss/loss11 = 7.69776e-05 (* 0.0454545 = 3.49898e-06 loss) | |
| I0407 16:54:48.157256 1004 solver.cpp:245] Train net output #33: loss/loss12 = 8.25802e-05 (* 0.0454545 = 3.75364e-06 loss) | |
| I0407 16:54:48.157270 1004 solver.cpp:245] Train net output #34: loss/loss13 = 7.34345e-05 (* 0.0454545 = 3.33793e-06 loss) | |
| I0407 16:54:48.157284 1004 solver.cpp:245] Train net output #35: loss/loss14 = 6.28134e-05 (* 0.0454545 = 2.85515e-06 loss) | |
| I0407 16:54:48.157299 1004 solver.cpp:245] Train net output #36: loss/loss15 = 6.66097e-05 (* 0.0454545 = 3.02771e-06 loss) | |
| I0407 16:54:48.157312 1004 solver.cpp:245] Train net output #37: loss/loss16 = 6.73182e-05 (* 0.0454545 = 3.05992e-06 loss) | |
| I0407 16:54:48.157326 1004 solver.cpp:245] Train net output #38: loss/loss17 = 7.07418e-05 (* 0.0454545 = 3.21554e-06 loss) | |
| I0407 16:54:48.157366 1004 solver.cpp:245] Train net output #39: loss/loss18 = 7.8093e-05 (* 0.0454545 = 3.54968e-06 loss) | |
| I0407 16:54:48.157382 1004 solver.cpp:245] Train net output #40: loss/loss19 = 5.28093e-05 (* 0.0454545 = 2.40042e-06 loss) | |
| I0407 16:54:48.157395 1004 solver.cpp:245] Train net output #41: loss/loss20 = 6.09378e-05 (* 0.0454545 = 2.7699e-06 loss) | |
| I0407 16:54:48.157409 1004 solver.cpp:245] Train net output #42: loss/loss21 = 7.28751e-05 (* 0.0454545 = 3.3125e-06 loss) | |
| I0407 16:54:48.157423 1004 solver.cpp:245] Train net output #43: loss/loss22 = 6.58974e-05 (* 0.0454545 = 2.99533e-06 loss) | |
| I0407 16:54:48.157436 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:54:48.157449 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000104001 | |
| I0407 16:54:48.157461 1004 sgd_solver.cpp:106] Iteration 76000, lr = 0.000848 | |
| I0407 16:55:27.031545 1004 solver.cpp:229] Iteration 76500, loss = 0.972834 | |
| I0407 16:55:27.031682 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.25 | |
| I0407 16:55:27.031702 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:55:27.031715 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 16:55:27.031728 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 16:55:27.031740 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.0625 | |
| I0407 16:55:27.031752 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.25 | |
| I0407 16:55:27.031764 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.5625 | |
| I0407 16:55:27.031777 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 16:55:27.031790 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.875 | |
| I0407 16:55:27.031801 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:55:27.031812 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:55:27.031824 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:55:27.031836 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:55:27.031847 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:55:27.031860 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:55:27.031872 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:55:27.031883 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:55:27.031894 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:55:27.031906 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:55:27.031918 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:55:27.031929 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:55:27.031940 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:55:27.031955 1004 solver.cpp:245] Train net output #22: loss/loss01 = 2.90856 (* 0.0454545 = 0.132207 loss) | |
| I0407 16:55:27.031970 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.43952 (* 0.0454545 = 0.156342 loss) | |
| I0407 16:55:27.031985 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.38962 (* 0.0454545 = 0.154074 loss) | |
| I0407 16:55:27.031998 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.27976 (* 0.0454545 = 0.14908 loss) | |
| I0407 16:55:27.032011 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.59362 (* 0.0454545 = 0.163346 loss) | |
| I0407 16:55:27.032026 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.94734 (* 0.0454545 = 0.13397 loss) | |
| I0407 16:55:27.032039 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.8468 (* 0.0454545 = 0.0839456 loss) | |
| I0407 16:55:27.032053 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.953202 (* 0.0454545 = 0.0433274 loss) | |
| I0407 16:55:27.032066 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.607895 (* 0.0454545 = 0.0276316 loss) | |
| I0407 16:55:27.032083 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0300199 (* 0.0454545 = 0.00136454 loss) | |
| I0407 16:55:27.032099 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000238388 (* 0.0454545 = 1.08358e-05 loss) | |
| I0407 16:55:27.032112 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000232186 (* 0.0454545 = 1.05539e-05 loss) | |
| I0407 16:55:27.032127 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000237489 (* 0.0454545 = 1.0795e-05 loss) | |
| I0407 16:55:27.032141 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000224224 (* 0.0454545 = 1.0192e-05 loss) | |
| I0407 16:55:27.032155 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000273373 (* 0.0454545 = 1.2426e-05 loss) | |
| I0407 16:55:27.032171 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000243469 (* 0.0454545 = 1.10668e-05 loss) | |
| I0407 16:55:27.032186 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000282889 (* 0.0454545 = 1.28586e-05 loss) | |
| I0407 16:55:27.032217 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000284973 (* 0.0454545 = 1.29533e-05 loss) | |
| I0407 16:55:27.032232 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000246461 (* 0.0454545 = 1.12028e-05 loss) | |
| I0407 16:55:27.032246 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000259253 (* 0.0454545 = 1.17842e-05 loss) | |
| I0407 16:55:27.032260 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000289786 (* 0.0454545 = 1.31721e-05 loss) | |
| I0407 16:55:27.032274 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000256954 (* 0.0454545 = 1.16797e-05 loss) | |
| I0407 16:55:27.032286 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:55:27.032299 1004 solver.cpp:245] Train net output #45: total_confidence = 5.67946e-05 | |
| I0407 16:55:27.032311 1004 sgd_solver.cpp:106] Iteration 76500, lr = 0.000847 | |
| I0407 16:56:05.910658 1004 solver.cpp:229] Iteration 77000, loss = 0.975022 | |
| I0407 16:56:05.910779 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:56:05.910809 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:56:05.910830 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 16:56:05.910852 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 16:56:05.910876 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 16:56:05.910897 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 16:56:05.910919 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 16:56:05.910941 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 1 | |
| I0407 16:56:05.910964 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:56:05.910985 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:56:05.911006 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:56:05.911026 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:56:05.911046 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:56:05.911067 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:56:05.911085 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:56:05.911106 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:56:05.911126 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:56:05.911149 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:56:05.911171 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:56:05.911191 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:56:05.911212 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:56:05.911233 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:56:05.911259 1004 solver.cpp:245] Train net output #22: loss/loss01 = 2.84411 (* 0.0454545 = 0.129278 loss) | |
| I0407 16:56:05.911284 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.32545 (* 0.0454545 = 0.151157 loss) | |
| I0407 16:56:05.911310 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.24176 (* 0.0454545 = 0.147353 loss) | |
| I0407 16:56:05.911356 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.53402 (* 0.0454545 = 0.160637 loss) | |
| I0407 16:56:05.911383 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.03392 (* 0.0454545 = 0.137905 loss) | |
| I0407 16:56:05.911412 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.71941 (* 0.0454545 = 0.123609 loss) | |
| I0407 16:56:05.911437 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.34659 (* 0.0454545 = 0.0612085 loss) | |
| I0407 16:56:05.911463 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.122992 (* 0.0454545 = 0.00559055 loss) | |
| I0407 16:56:05.911489 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0464075 (* 0.0454545 = 0.00210943 loss) | |
| I0407 16:56:05.911515 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0153047 (* 0.0454545 = 0.00069567 loss) | |
| I0407 16:56:05.911541 1004 solver.cpp:245] Train net output #32: loss/loss11 = 4.14572e-05 (* 0.0454545 = 1.88442e-06 loss) | |
| I0407 16:56:05.911567 1004 solver.cpp:245] Train net output #33: loss/loss12 = 3.91842e-05 (* 0.0454545 = 1.7811e-06 loss) | |
| I0407 16:56:05.911592 1004 solver.cpp:245] Train net output #34: loss/loss13 = 3.51784e-05 (* 0.0454545 = 1.59902e-06 loss) | |
| I0407 16:56:05.911618 1004 solver.cpp:245] Train net output #35: loss/loss14 = 3.38966e-05 (* 0.0454545 = 1.54075e-06 loss) | |
| I0407 16:56:05.911643 1004 solver.cpp:245] Train net output #36: loss/loss15 = 3.84986e-05 (* 0.0454545 = 1.74994e-06 loss) | |
| I0407 16:56:05.911669 1004 solver.cpp:245] Train net output #37: loss/loss16 = 3.40233e-05 (* 0.0454545 = 1.54652e-06 loss) | |
| I0407 16:56:05.911695 1004 solver.cpp:245] Train net output #38: loss/loss17 = 3.51785e-05 (* 0.0454545 = 1.59902e-06 loss) | |
| I0407 16:56:05.911744 1004 solver.cpp:245] Train net output #39: loss/loss18 = 3.77013e-05 (* 0.0454545 = 1.71369e-06 loss) | |
| I0407 16:56:05.911772 1004 solver.cpp:245] Train net output #40: loss/loss19 = 3.10051e-05 (* 0.0454545 = 1.40932e-06 loss) | |
| I0407 16:56:05.911803 1004 solver.cpp:245] Train net output #41: loss/loss20 = 3.23689e-05 (* 0.0454545 = 1.47132e-06 loss) | |
| I0407 16:56:05.911830 1004 solver.cpp:245] Train net output #42: loss/loss21 = 3.74033e-05 (* 0.0454545 = 1.70015e-06 loss) | |
| I0407 16:56:05.911855 1004 solver.cpp:245] Train net output #43: loss/loss22 = 4.08388e-05 (* 0.0454545 = 1.85631e-06 loss) | |
| I0407 16:56:05.911876 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:56:05.911896 1004 solver.cpp:245] Train net output #45: total_confidence = 8.40021e-07 | |
| I0407 16:56:05.911918 1004 sgd_solver.cpp:106] Iteration 77000, lr = 0.000846 | |
| I0407 16:56:44.824825 1004 solver.cpp:229] Iteration 77500, loss = 0.970292 | |
| I0407 16:56:44.824949 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 16:56:44.824968 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:56:44.824981 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.125 | |
| I0407 16:56:44.824993 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 16:56:44.825006 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.3125 | |
| I0407 16:56:44.825017 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5625 | |
| I0407 16:56:44.825029 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 16:56:44.825042 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:56:44.825053 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:56:44.825064 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:56:44.825076 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:56:44.825088 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:56:44.825099 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:56:44.825110 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:56:44.825122 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:56:44.825134 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:56:44.825145 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:56:44.825156 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:56:44.825168 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:56:44.825179 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:56:44.825192 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:56:44.825203 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:56:44.825219 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.23668 (* 0.0454545 = 0.147122 loss) | |
| I0407 16:56:44.825233 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.53602 (* 0.0454545 = 0.160728 loss) | |
| I0407 16:56:44.825248 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.35284 (* 0.0454545 = 0.152402 loss) | |
| I0407 16:56:44.825260 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.50272 (* 0.0454545 = 0.159215 loss) | |
| I0407 16:56:44.825274 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.02149 (* 0.0454545 = 0.13734 loss) | |
| I0407 16:56:44.825289 1004 solver.cpp:245] Train net output #27: loss/loss06 = 1.77585 (* 0.0454545 = 0.0807205 loss) | |
| I0407 16:56:44.825302 1004 solver.cpp:245] Train net output #28: loss/loss07 = 0.86912 (* 0.0454545 = 0.0395054 loss) | |
| I0407 16:56:44.825315 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.486245 (* 0.0454545 = 0.022102 loss) | |
| I0407 16:56:44.825330 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0393365 (* 0.0454545 = 0.00178802 loss) | |
| I0407 16:56:44.825345 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0104495 (* 0.0454545 = 0.000474979 loss) | |
| I0407 16:56:44.825361 1004 solver.cpp:245] Train net output #32: loss/loss11 = 7.88185e-05 (* 0.0454545 = 3.58266e-06 loss) | |
| I0407 16:56:44.825374 1004 solver.cpp:245] Train net output #33: loss/loss12 = 6.53775e-05 (* 0.0454545 = 2.9717e-06 loss) | |
| I0407 16:56:44.825388 1004 solver.cpp:245] Train net output #34: loss/loss13 = 6.32711e-05 (* 0.0454545 = 2.87596e-06 loss) | |
| I0407 16:56:44.825402 1004 solver.cpp:245] Train net output #35: loss/loss14 = 6.40428e-05 (* 0.0454545 = 2.91104e-06 loss) | |
| I0407 16:56:44.825417 1004 solver.cpp:245] Train net output #36: loss/loss15 = 7.47013e-05 (* 0.0454545 = 3.39551e-06 loss) | |
| I0407 16:56:44.825431 1004 solver.cpp:245] Train net output #37: loss/loss16 = 6.7526e-05 (* 0.0454545 = 3.06936e-06 loss) | |
| I0407 16:56:44.825445 1004 solver.cpp:245] Train net output #38: loss/loss17 = 8.0557e-05 (* 0.0454545 = 3.66168e-06 loss) | |
| I0407 16:56:44.825476 1004 solver.cpp:245] Train net output #39: loss/loss18 = 7.58986e-05 (* 0.0454545 = 3.44994e-06 loss) | |
| I0407 16:56:44.825492 1004 solver.cpp:245] Train net output #40: loss/loss19 = 6.52437e-05 (* 0.0454545 = 2.96562e-06 loss) | |
| I0407 16:56:44.825506 1004 solver.cpp:245] Train net output #41: loss/loss20 = 5.55786e-05 (* 0.0454545 = 2.5263e-06 loss) | |
| I0407 16:56:44.825520 1004 solver.cpp:245] Train net output #42: loss/loss21 = 7.00061e-05 (* 0.0454545 = 3.1821e-06 loss) | |
| I0407 16:56:44.825534 1004 solver.cpp:245] Train net output #43: loss/loss22 = 7.09569e-05 (* 0.0454545 = 3.22531e-06 loss) | |
| I0407 16:56:44.825546 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:56:44.825557 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000107102 | |
| I0407 16:56:44.825572 1004 sgd_solver.cpp:106] Iteration 77500, lr = 0.000845 | |
| I0407 16:57:24.071579 1004 solver.cpp:229] Iteration 78000, loss = 0.97727 | |
| I0407 16:57:24.071748 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:57:24.071768 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:57:24.071781 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.1875 | |
| I0407 16:57:24.071794 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 16:57:24.071806 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.1875 | |
| I0407 16:57:24.071817 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 16:57:24.071830 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 16:57:24.071841 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 16:57:24.071853 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:57:24.071866 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:57:24.071877 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:57:24.071887 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:57:24.071899 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:57:24.071910 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:57:24.071925 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:57:24.071938 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:57:24.071949 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:57:24.071960 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:57:24.071971 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:57:24.071982 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:57:24.071993 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:57:24.072005 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:57:24.072021 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.22341 (* 0.0454545 = 0.146519 loss) | |
| I0407 16:57:24.072036 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.40654 (* 0.0454545 = 0.154843 loss) | |
| I0407 16:57:24.072048 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.32171 (* 0.0454545 = 0.150987 loss) | |
| I0407 16:57:24.072062 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.6724 (* 0.0454545 = 0.166927 loss) | |
| I0407 16:57:24.072077 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.1532 (* 0.0454545 = 0.143327 loss) | |
| I0407 16:57:24.072090 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.87114 (* 0.0454545 = 0.130506 loss) | |
| I0407 16:57:24.072104 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.43129 (* 0.0454545 = 0.0650589 loss) | |
| I0407 16:57:24.072118 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.971688 (* 0.0454545 = 0.0441676 loss) | |
| I0407 16:57:24.072131 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.339526 (* 0.0454545 = 0.015433 loss) | |
| I0407 16:57:24.072145 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.00938771 (* 0.0454545 = 0.000426714 loss) | |
| I0407 16:57:24.072160 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000122285 (* 0.0454545 = 5.55843e-06 loss) | |
| I0407 16:57:24.072175 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.00012021 (* 0.0454545 = 5.4641e-06 loss) | |
| I0407 16:57:24.072188 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000106582 (* 0.0454545 = 4.84462e-06 loss) | |
| I0407 16:57:24.072202 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000113257 (* 0.0454545 = 5.14805e-06 loss) | |
| I0407 16:57:24.072216 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000117479 (* 0.0454545 = 5.33997e-06 loss) | |
| I0407 16:57:24.072230 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000104897 (* 0.0454545 = 4.76802e-06 loss) | |
| I0407 16:57:24.072244 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000124057 (* 0.0454545 = 5.63897e-06 loss) | |
| I0407 16:57:24.072273 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000112424 (* 0.0454545 = 5.1102e-06 loss) | |
| I0407 16:57:24.072288 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000107022 (* 0.0454545 = 4.86464e-06 loss) | |
| I0407 16:57:24.072302 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000110313 (* 0.0454545 = 5.01422e-06 loss) | |
| I0407 16:57:24.072317 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000119812 (* 0.0454545 = 5.44601e-06 loss) | |
| I0407 16:57:24.072331 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000102519 (* 0.0454545 = 4.65997e-06 loss) | |
| I0407 16:57:24.072343 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:57:24.072355 1004 solver.cpp:245] Train net output #45: total_confidence = 2.19217e-06 | |
| I0407 16:57:24.072367 1004 sgd_solver.cpp:106] Iteration 78000, lr = 0.000844 | |
| I0407 16:58:03.595341 1004 solver.cpp:229] Iteration 78500, loss = 0.976837 | |
| I0407 16:58:03.595464 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.25 | |
| I0407 16:58:03.595484 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.125 | |
| I0407 16:58:03.595496 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 16:58:03.595510 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 16:58:03.595521 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 16:58:03.595533 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 16:58:03.595552 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.6875 | |
| I0407 16:58:03.595578 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:58:03.595599 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:58:03.595613 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 16:58:03.595625 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:58:03.595638 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:58:03.595649 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:58:03.595660 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:58:03.595671 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:58:03.595684 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:58:03.595695 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:58:03.595705 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:58:03.595716 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:58:03.595728 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:58:03.595741 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:58:03.595752 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:58:03.595767 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.00344 (* 0.0454545 = 0.13652 loss) | |
| I0407 16:58:03.595782 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.45286 (* 0.0454545 = 0.156948 loss) | |
| I0407 16:58:03.595795 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.71782 (* 0.0454545 = 0.168992 loss) | |
| I0407 16:58:03.595809 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.32549 (* 0.0454545 = 0.151158 loss) | |
| I0407 16:58:03.595824 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.10183 (* 0.0454545 = 0.140992 loss) | |
| I0407 16:58:03.595836 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.68581 (* 0.0454545 = 0.122082 loss) | |
| I0407 16:58:03.595850 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.72268 (* 0.0454545 = 0.0783037 loss) | |
| I0407 16:58:03.595863 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.268579 (* 0.0454545 = 0.0122081 loss) | |
| I0407 16:58:03.595877 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.301251 (* 0.0454545 = 0.0136932 loss) | |
| I0407 16:58:03.595891 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.374709 (* 0.0454545 = 0.0170322 loss) | |
| I0407 16:58:03.595906 1004 solver.cpp:245] Train net output #32: loss/loss11 = 2.43455e-05 (* 0.0454545 = 1.10662e-06 loss) | |
| I0407 16:58:03.595922 1004 solver.cpp:245] Train net output #33: loss/loss12 = 2.85978e-05 (* 0.0454545 = 1.2999e-06 loss) | |
| I0407 16:58:03.595937 1004 solver.cpp:245] Train net output #34: loss/loss13 = 2.55717e-05 (* 0.0454545 = 1.16235e-06 loss) | |
| I0407 16:58:03.595952 1004 solver.cpp:245] Train net output #35: loss/loss14 = 3.46732e-05 (* 0.0454545 = 1.57605e-06 loss) | |
| I0407 16:58:03.595973 1004 solver.cpp:245] Train net output #36: loss/loss15 = 2.73978e-05 (* 0.0454545 = 1.24536e-06 loss) | |
| I0407 16:58:03.596004 1004 solver.cpp:245] Train net output #37: loss/loss16 = 2.90191e-05 (* 0.0454545 = 1.31905e-06 loss) | |
| I0407 16:58:03.596021 1004 solver.cpp:245] Train net output #38: loss/loss17 = 2.89781e-05 (* 0.0454545 = 1.31718e-06 loss) | |
| I0407 16:58:03.596053 1004 solver.cpp:245] Train net output #39: loss/loss18 = 3.00179e-05 (* 0.0454545 = 1.36445e-06 loss) | |
| I0407 16:58:03.596074 1004 solver.cpp:245] Train net output #40: loss/loss19 = 3.52919e-05 (* 0.0454545 = 1.60418e-06 loss) | |
| I0407 16:58:03.596106 1004 solver.cpp:245] Train net output #41: loss/loss20 = 3.20306e-05 (* 0.0454545 = 1.45594e-06 loss) | |
| I0407 16:58:03.596124 1004 solver.cpp:245] Train net output #42: loss/loss21 = 3.20827e-05 (* 0.0454545 = 1.4583e-06 loss) | |
| I0407 16:58:03.596139 1004 solver.cpp:245] Train net output #43: loss/loss22 = 3.33612e-05 (* 0.0454545 = 1.51642e-06 loss) | |
| I0407 16:58:03.596151 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:58:03.596163 1004 solver.cpp:245] Train net output #45: total_confidence = 9.33661e-05 | |
| I0407 16:58:03.596175 1004 sgd_solver.cpp:106] Iteration 78500, lr = 0.000843 | |
| I0407 16:58:43.225256 1004 solver.cpp:229] Iteration 79000, loss = 0.968364 | |
| I0407 16:58:43.225381 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:58:43.225400 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.125 | |
| I0407 16:58:43.225414 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:58:43.225425 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.125 | |
| I0407 16:58:43.225437 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 16:58:43.225450 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5 | |
| I0407 16:58:43.225461 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 16:58:43.225472 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 16:58:43.225484 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 16:58:43.225495 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 16:58:43.225507 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:58:43.225518 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:58:43.225530 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:58:43.225541 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:58:43.225553 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:58:43.225564 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:58:43.225575 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:58:43.225586 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:58:43.225597 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:58:43.225610 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:58:43.225620 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:58:43.225631 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:58:43.225647 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.33556 (* 0.0454545 = 0.151616 loss) | |
| I0407 16:58:43.225662 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.78543 (* 0.0454545 = 0.172065 loss) | |
| I0407 16:58:43.225677 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.40855 (* 0.0454545 = 0.154934 loss) | |
| I0407 16:58:43.225690 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.24522 (* 0.0454545 = 0.14751 loss) | |
| I0407 16:58:43.225704 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.09475 (* 0.0454545 = 0.14067 loss) | |
| I0407 16:58:43.225718 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.34484 (* 0.0454545 = 0.106583 loss) | |
| I0407 16:58:43.225731 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.37217 (* 0.0454545 = 0.0623713 loss) | |
| I0407 16:58:43.225745 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.911907 (* 0.0454545 = 0.0414503 loss) | |
| I0407 16:58:43.225759 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0538224 (* 0.0454545 = 0.00244647 loss) | |
| I0407 16:58:43.225774 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0183352 (* 0.0454545 = 0.000833418 loss) | |
| I0407 16:58:43.225787 1004 solver.cpp:245] Train net output #32: loss/loss11 = 1.21449e-05 (* 0.0454545 = 5.52042e-07 loss) | |
| I0407 16:58:43.225803 1004 solver.cpp:245] Train net output #33: loss/loss12 = 1.38588e-05 (* 0.0454545 = 6.29945e-07 loss) | |
| I0407 16:58:43.225817 1004 solver.cpp:245] Train net output #34: loss/loss13 = 1.05057e-05 (* 0.0454545 = 4.77531e-07 loss) | |
| I0407 16:58:43.225831 1004 solver.cpp:245] Train net output #35: loss/loss14 = 9.79786e-06 (* 0.0454545 = 4.45357e-07 loss) | |
| I0407 16:58:43.225844 1004 solver.cpp:245] Train net output #36: loss/loss15 = 9.5147e-06 (* 0.0454545 = 4.32486e-07 loss) | |
| I0407 16:58:43.225859 1004 solver.cpp:245] Train net output #37: loss/loss16 = 9.90961e-06 (* 0.0454545 = 4.50437e-07 loss) | |
| I0407 16:58:43.225873 1004 solver.cpp:245] Train net output #38: loss/loss17 = 9.85746e-06 (* 0.0454545 = 4.48066e-07 loss) | |
| I0407 16:58:43.225903 1004 solver.cpp:245] Train net output #39: loss/loss18 = 8.94842e-06 (* 0.0454545 = 4.06746e-07 loss) | |
| I0407 16:58:43.225922 1004 solver.cpp:245] Train net output #40: loss/loss19 = 9.15706e-06 (* 0.0454545 = 4.1623e-07 loss) | |
| I0407 16:58:43.225937 1004 solver.cpp:245] Train net output #41: loss/loss20 = 8.3598e-06 (* 0.0454545 = 3.79991e-07 loss) | |
| I0407 16:58:43.225951 1004 solver.cpp:245] Train net output #42: loss/loss21 = 8.62803e-06 (* 0.0454545 = 3.92183e-07 loss) | |
| I0407 16:58:43.225965 1004 solver.cpp:245] Train net output #43: loss/loss22 = 9.09743e-06 (* 0.0454545 = 4.1352e-07 loss) | |
| I0407 16:58:43.225977 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:58:43.225989 1004 solver.cpp:245] Train net output #45: total_confidence = 0.000311897 | |
| I0407 16:58:43.226002 1004 sgd_solver.cpp:106] Iteration 79000, lr = 0.000842 | |
| I0407 16:59:22.218101 1004 solver.cpp:229] Iteration 79500, loss = 0.962143 | |
| I0407 16:59:22.218216 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 16:59:22.218235 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 16:59:22.218248 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 16:59:22.218261 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 16:59:22.218272 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 16:59:22.218284 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.4375 | |
| I0407 16:59:22.218297 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 16:59:22.218307 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 16:59:22.218319 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 16:59:22.218330 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 16:59:22.218343 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 16:59:22.218354 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 16:59:22.218365 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 16:59:22.218376 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 16:59:22.218389 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 16:59:22.218400 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 16:59:22.218410 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 16:59:22.218422 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 16:59:22.218433 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 16:59:22.218446 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 16:59:22.218457 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 16:59:22.218468 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 16:59:22.218484 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.6233 (* 0.0454545 = 0.164696 loss) | |
| I0407 16:59:22.218498 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.75532 (* 0.0454545 = 0.170696 loss) | |
| I0407 16:59:22.218513 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.55156 (* 0.0454545 = 0.161435 loss) | |
| I0407 16:59:22.218526 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.62541 (* 0.0454545 = 0.164792 loss) | |
| I0407 16:59:22.218540 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.14321 (* 0.0454545 = 0.142873 loss) | |
| I0407 16:59:22.218554 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.38344 (* 0.0454545 = 0.108338 loss) | |
| I0407 16:59:22.218567 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.05343 (* 0.0454545 = 0.047883 loss) | |
| I0407 16:59:22.218581 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.42503 (* 0.0454545 = 0.0193195 loss) | |
| I0407 16:59:22.218595 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.452451 (* 0.0454545 = 0.0205659 loss) | |
| I0407 16:59:22.218610 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.499007 (* 0.0454545 = 0.0226821 loss) | |
| I0407 16:59:22.218623 1004 solver.cpp:245] Train net output #32: loss/loss11 = 5.88947e-05 (* 0.0454545 = 2.67703e-06 loss) | |
| I0407 16:59:22.218638 1004 solver.cpp:245] Train net output #33: loss/loss12 = 5.55449e-05 (* 0.0454545 = 2.52477e-06 loss) | |
| I0407 16:59:22.218652 1004 solver.cpp:245] Train net output #34: loss/loss13 = 5.05479e-05 (* 0.0454545 = 2.29763e-06 loss) | |
| I0407 16:59:22.218665 1004 solver.cpp:245] Train net output #35: loss/loss14 = 4.98882e-05 (* 0.0454545 = 2.26765e-06 loss) | |
| I0407 16:59:22.218679 1004 solver.cpp:245] Train net output #36: loss/loss15 = 5.23665e-05 (* 0.0454545 = 2.3803e-06 loss) | |
| I0407 16:59:22.218693 1004 solver.cpp:245] Train net output #37: loss/loss16 = 5.07268e-05 (* 0.0454545 = 2.30577e-06 loss) | |
| I0407 16:59:22.218708 1004 solver.cpp:245] Train net output #38: loss/loss17 = 4.75595e-05 (* 0.0454545 = 2.1618e-06 loss) | |
| I0407 16:59:22.218739 1004 solver.cpp:245] Train net output #39: loss/loss18 = 5.64879e-05 (* 0.0454545 = 2.56763e-06 loss) | |
| I0407 16:59:22.218754 1004 solver.cpp:245] Train net output #40: loss/loss19 = 4.92887e-05 (* 0.0454545 = 2.24039e-06 loss) | |
| I0407 16:59:22.218767 1004 solver.cpp:245] Train net output #41: loss/loss20 = 4.72169e-05 (* 0.0454545 = 2.14622e-06 loss) | |
| I0407 16:59:22.218781 1004 solver.cpp:245] Train net output #42: loss/loss21 = 5.29256e-05 (* 0.0454545 = 2.40571e-06 loss) | |
| I0407 16:59:22.218796 1004 solver.cpp:245] Train net output #43: loss/loss22 = 5.40886e-05 (* 0.0454545 = 2.45857e-06 loss) | |
| I0407 16:59:22.218806 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 16:59:22.218818 1004 solver.cpp:245] Train net output #45: total_confidence = 5.21125e-05 | |
| I0407 16:59:22.218830 1004 sgd_solver.cpp:106] Iteration 79500, lr = 0.000841 | |
| I0407 17:00:01.638530 1004 solver.cpp:338] Iteration 80000, Testing net (#0) | |
| I0407 17:00:09.624562 1004 solver.cpp:393] Test loss: 0.869783 | |
| I0407 17:00:09.624608 1004 solver.cpp:406] Test net output #0: loss/accuracy01 = 0.321 | |
| I0407 17:00:09.624624 1004 solver.cpp:406] Test net output #1: loss/accuracy02 = 0.092 | |
| I0407 17:00:09.624637 1004 solver.cpp:406] Test net output #2: loss/accuracy03 = 0.084 | |
| I0407 17:00:09.624650 1004 solver.cpp:406] Test net output #3: loss/accuracy04 = 0.083 | |
| I0407 17:00:09.624660 1004 solver.cpp:406] Test net output #4: loss/accuracy05 = 0.205 | |
| I0407 17:00:09.624672 1004 solver.cpp:406] Test net output #5: loss/accuracy06 = 0.497 | |
| I0407 17:00:09.624686 1004 solver.cpp:406] Test net output #6: loss/accuracy07 = 0.894 | |
| I0407 17:00:09.624696 1004 solver.cpp:406] Test net output #7: loss/accuracy08 = 0.97 | |
| I0407 17:00:09.624708 1004 solver.cpp:406] Test net output #8: loss/accuracy09 = 0.995 | |
| I0407 17:00:09.624719 1004 solver.cpp:406] Test net output #9: loss/accuracy10 = 0.998 | |
| I0407 17:00:09.624732 1004 solver.cpp:406] Test net output #10: loss/accuracy11 = 1 | |
| I0407 17:00:09.624742 1004 solver.cpp:406] Test net output #11: loss/accuracy12 = 1 | |
| I0407 17:00:09.624753 1004 solver.cpp:406] Test net output #12: loss/accuracy13 = 1 | |
| I0407 17:00:09.624764 1004 solver.cpp:406] Test net output #13: loss/accuracy14 = 1 | |
| I0407 17:00:09.624775 1004 solver.cpp:406] Test net output #14: loss/accuracy15 = 1 | |
| I0407 17:00:09.624786 1004 solver.cpp:406] Test net output #15: loss/accuracy16 = 1 | |
| I0407 17:00:09.624797 1004 solver.cpp:406] Test net output #16: loss/accuracy17 = 1 | |
| I0407 17:00:09.624809 1004 solver.cpp:406] Test net output #17: loss/accuracy18 = 1 | |
| I0407 17:00:09.624819 1004 solver.cpp:406] Test net output #18: loss/accuracy19 = 1 | |
| I0407 17:00:09.624830 1004 solver.cpp:406] Test net output #19: loss/accuracy20 = 1 | |
| I0407 17:00:09.624840 1004 solver.cpp:406] Test net output #20: loss/accuracy21 = 1 | |
| I0407 17:00:09.624851 1004 solver.cpp:406] Test net output #21: loss/accuracy22 = 1 | |
| I0407 17:00:09.624867 1004 solver.cpp:406] Test net output #22: loss/loss01 = 2.93912 (* 0.0454545 = 0.133596 loss) | |
| I0407 17:00:09.624881 1004 solver.cpp:406] Test net output #23: loss/loss02 = 3.17453 (* 0.0454545 = 0.144297 loss) | |
| I0407 17:00:09.624896 1004 solver.cpp:406] Test net output #24: loss/loss03 = 3.27611 (* 0.0454545 = 0.148914 loss) | |
| I0407 17:00:09.624908 1004 solver.cpp:406] Test net output #25: loss/loss04 = 3.25077 (* 0.0454545 = 0.147762 loss) | |
| I0407 17:00:09.624925 1004 solver.cpp:406] Test net output #26: loss/loss05 = 3.16142 (* 0.0454545 = 0.143701 loss) | |
| I0407 17:00:09.624939 1004 solver.cpp:406] Test net output #27: loss/loss06 = 2.2609 (* 0.0454545 = 0.102768 loss) | |
| I0407 17:00:09.624953 1004 solver.cpp:406] Test net output #28: loss/loss07 = 0.734126 (* 0.0454545 = 0.0333693 loss) | |
| I0407 17:00:09.624966 1004 solver.cpp:406] Test net output #29: loss/loss08 = 0.254448 (* 0.0454545 = 0.0115658 loss) | |
| I0407 17:00:09.624980 1004 solver.cpp:406] Test net output #30: loss/loss09 = 0.0548584 (* 0.0454545 = 0.00249357 loss) | |
| I0407 17:00:09.624994 1004 solver.cpp:406] Test net output #31: loss/loss10 = 0.0277361 (* 0.0454545 = 0.00126073 loss) | |
| I0407 17:00:09.625008 1004 solver.cpp:406] Test net output #32: loss/loss11 = 0.000109576 (* 0.0454545 = 4.98073e-06 loss) | |
| I0407 17:00:09.625022 1004 solver.cpp:406] Test net output #33: loss/loss12 = 0.000111511 (* 0.0454545 = 5.06868e-06 loss) | |
| I0407 17:00:09.625036 1004 solver.cpp:406] Test net output #34: loss/loss13 = 0.000100709 (* 0.0454545 = 4.57767e-06 loss) | |
| I0407 17:00:09.625049 1004 solver.cpp:406] Test net output #35: loss/loss14 = 0.00010135 (* 0.0454545 = 4.60684e-06 loss) | |
| I0407 17:00:09.625063 1004 solver.cpp:406] Test net output #36: loss/loss15 = 0.000100127 (* 0.0454545 = 4.55122e-06 loss) | |
| I0407 17:00:09.625077 1004 solver.cpp:406] Test net output #37: loss/loss16 = 0.000100105 (* 0.0454545 = 4.55022e-06 loss) | |
| I0407 17:00:09.625092 1004 solver.cpp:406] Test net output #38: loss/loss17 = 0.000101097 (* 0.0454545 = 4.59531e-06 loss) | |
| I0407 17:00:09.625138 1004 solver.cpp:406] Test net output #39: loss/loss18 = 0.00010271 (* 0.0454545 = 4.66864e-06 loss) | |
| I0407 17:00:09.625154 1004 solver.cpp:406] Test net output #40: loss/loss19 = 9.7015e-05 (* 0.0454545 = 4.40977e-06 loss) | |
| I0407 17:00:09.625169 1004 solver.cpp:406] Test net output #41: loss/loss20 = 9.89693e-05 (* 0.0454545 = 4.49861e-06 loss) | |
| I0407 17:00:09.625182 1004 solver.cpp:406] Test net output #42: loss/loss21 = 9.73527e-05 (* 0.0454545 = 4.42512e-06 loss) | |
| I0407 17:00:09.625195 1004 solver.cpp:406] Test net output #43: loss/loss22 = 9.92332e-05 (* 0.0454545 = 4.5106e-06 loss) | |
| I0407 17:00:09.625207 1004 solver.cpp:406] Test net output #44: total_accuracy = 0 | |
| I0407 17:00:09.625219 1004 solver.cpp:406] Test net output #45: total_confidence = 0.000155281 | |
| I0407 17:00:09.647954 1004 solver.cpp:229] Iteration 80000, loss = 0.965318 | |
| I0407 17:00:09.648007 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 17:00:09.648027 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 17:00:09.648041 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 17:00:09.648064 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 17:00:09.648092 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.25 | |
| I0407 17:00:09.648108 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.3125 | |
| I0407 17:00:09.648120 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 17:00:09.648133 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 17:00:09.648144 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.875 | |
| I0407 17:00:09.648156 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 17:00:09.648167 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 17:00:09.648180 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 17:00:09.648191 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 17:00:09.648203 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 17:00:09.648214 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 17:00:09.648226 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 17:00:09.648237 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 17:00:09.648248 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 17:00:09.648259 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 17:00:09.648270 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 17:00:09.648283 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 17:00:09.648293 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 17:00:09.648308 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.16311 (* 0.0454545 = 0.143778 loss) | |
| I0407 17:00:09.648322 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.39723 (* 0.0454545 = 0.15442 loss) | |
| I0407 17:00:09.648336 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.53058 (* 0.0454545 = 0.160481 loss) | |
| I0407 17:00:09.648350 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.04101 (* 0.0454545 = 0.138228 loss) | |
| I0407 17:00:09.648371 1004 solver.cpp:245] Train net output #26: loss/loss05 = 2.8294 (* 0.0454545 = 0.128609 loss) | |
| I0407 17:00:09.648406 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.80908 (* 0.0454545 = 0.127685 loss) | |
| I0407 17:00:09.648422 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.08338 (* 0.0454545 = 0.0492446 loss) | |
| I0407 17:00:09.648437 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.755726 (* 0.0454545 = 0.0343512 loss) | |
| I0407 17:00:09.648450 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.717777 (* 0.0454545 = 0.0326262 loss) | |
| I0407 17:00:09.648464 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.356418 (* 0.0454545 = 0.0162008 loss) | |
| I0407 17:00:09.648497 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000278658 (* 0.0454545 = 1.26663e-05 loss) | |
| I0407 17:00:09.648514 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000312705 (* 0.0454545 = 1.42139e-05 loss) | |
| I0407 17:00:09.648529 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.00029047 (* 0.0454545 = 1.32032e-05 loss) | |
| I0407 17:00:09.648543 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000330707 (* 0.0454545 = 1.50321e-05 loss) | |
| I0407 17:00:09.648557 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000334506 (* 0.0454545 = 1.52048e-05 loss) | |
| I0407 17:00:09.648571 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000362865 (* 0.0454545 = 1.64939e-05 loss) | |
| I0407 17:00:09.648586 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000358434 (* 0.0454545 = 1.62925e-05 loss) | |
| I0407 17:00:09.648599 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000374105 (* 0.0454545 = 1.70048e-05 loss) | |
| I0407 17:00:09.648613 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000343843 (* 0.0454545 = 1.56292e-05 loss) | |
| I0407 17:00:09.648627 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000309174 (* 0.0454545 = 1.40534e-05 loss) | |
| I0407 17:00:09.648641 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000311824 (* 0.0454545 = 1.41738e-05 loss) | |
| I0407 17:00:09.648655 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000279588 (* 0.0454545 = 1.27086e-05 loss) | |
| I0407 17:00:09.648668 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 17:00:09.648679 1004 solver.cpp:245] Train net output #45: total_confidence = 0.00114305 | |
| I0407 17:00:09.648694 1004 sgd_solver.cpp:106] Iteration 80000, lr = 0.00084 | |
| I0407 17:00:48.489629 1004 solver.cpp:229] Iteration 80500, loss = 0.967568 | |
| I0407 17:00:48.489739 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 17:00:48.489758 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 17:00:48.489771 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 17:00:48.489784 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 17:00:48.489796 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 17:00:48.489809 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 17:00:48.489820 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.625 | |
| I0407 17:00:48.489831 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.8125 | |
| I0407 17:00:48.489843 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 1 | |
| I0407 17:00:48.489856 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 17:00:48.489868 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 17:00:48.489879 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 17:00:48.489892 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 17:00:48.489902 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 17:00:48.489914 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 17:00:48.489925 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 17:00:48.489938 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 17:00:48.489948 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 17:00:48.489959 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 17:00:48.489970 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 17:00:48.489982 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 17:00:48.489995 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 17:00:48.490010 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.29955 (* 0.0454545 = 0.14998 loss) | |
| I0407 17:00:48.490025 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.34291 (* 0.0454545 = 0.151951 loss) | |
| I0407 17:00:48.490038 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.30005 (* 0.0454545 = 0.150002 loss) | |
| I0407 17:00:48.490051 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.35007 (* 0.0454545 = 0.152276 loss) | |
| I0407 17:00:48.490066 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.18383 (* 0.0454545 = 0.14472 loss) | |
| I0407 17:00:48.490079 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.54467 (* 0.0454545 = 0.115667 loss) | |
| I0407 17:00:48.490092 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.41039 (* 0.0454545 = 0.0641088 loss) | |
| I0407 17:00:48.490106 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.763155 (* 0.0454545 = 0.0346888 loss) | |
| I0407 17:00:48.490120 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.0806254 (* 0.0454545 = 0.00366479 loss) | |
| I0407 17:00:48.490139 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.0277077 (* 0.0454545 = 0.00125944 loss) | |
| I0407 17:00:48.490152 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.000370918 (* 0.0454545 = 1.68599e-05 loss) | |
| I0407 17:00:48.490167 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000344544 (* 0.0454545 = 1.56611e-05 loss) | |
| I0407 17:00:48.490182 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000351508 (* 0.0454545 = 1.59776e-05 loss) | |
| I0407 17:00:48.490196 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000327163 (* 0.0454545 = 1.48711e-05 loss) | |
| I0407 17:00:48.490211 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.00037583 (* 0.0454545 = 1.70832e-05 loss) | |
| I0407 17:00:48.490224 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000382924 (* 0.0454545 = 1.74056e-05 loss) | |
| I0407 17:00:48.490238 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000350956 (* 0.0454545 = 1.59525e-05 loss) | |
| I0407 17:00:48.490269 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000393753 (* 0.0454545 = 1.78979e-05 loss) | |
| I0407 17:00:48.490285 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000335497 (* 0.0454545 = 1.52499e-05 loss) | |
| I0407 17:00:48.490299 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000314276 (* 0.0454545 = 1.42853e-05 loss) | |
| I0407 17:00:48.490314 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000363084 (* 0.0454545 = 1.65038e-05 loss) | |
| I0407 17:00:48.490326 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000373772 (* 0.0454545 = 1.69896e-05 loss) | |
| I0407 17:00:48.490339 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 17:00:48.490350 1004 solver.cpp:245] Train net output #45: total_confidence = 7.95353e-05 | |
| I0407 17:00:48.490363 1004 sgd_solver.cpp:106] Iteration 80500, lr = 0.000839 | |
| I0407 17:01:27.867372 1004 solver.cpp:229] Iteration 81000, loss = 0.962802 | |
| I0407 17:01:27.867523 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 17:01:27.867543 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 17:01:27.867557 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0407 17:01:27.867569 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.1875 | |
| I0407 17:01:27.867581 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.4375 | |
| I0407 17:01:27.867594 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.5 | |
| I0407 17:01:27.867604 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 17:01:27.867616 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 17:01:27.867629 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 17:01:27.867640 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 1 | |
| I0407 17:01:27.867651 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 17:01:27.867663 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 17:01:27.867674 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 17:01:27.867686 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 17:01:27.867697 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 17:01:27.867709 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 17:01:27.867722 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 17:01:27.867733 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 17:01:27.867744 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 17:01:27.867755 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 17:01:27.867768 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 17:01:27.867779 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 17:01:27.867794 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.01597 (* 0.0454545 = 0.13709 loss) | |
| I0407 17:01:27.867810 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.40168 (* 0.0454545 = 0.154622 loss) | |
| I0407 17:01:27.867823 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.21644 (* 0.0454545 = 0.146202 loss) | |
| I0407 17:01:27.867837 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.06292 (* 0.0454545 = 0.139224 loss) | |
| I0407 17:01:27.867851 1004 solver.cpp:245] Train net output #26: loss/loss05 = 2.2373 (* 0.0454545 = 0.101696 loss) | |
| I0407 17:01:27.867866 1004 solver.cpp:245] Train net output #27: loss/loss06 = 1.841 (* 0.0454545 = 0.0836817 loss) | |
| I0407 17:01:27.867878 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.71306 (* 0.0454545 = 0.0778664 loss) | |
| I0407 17:01:27.867892 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.690238 (* 0.0454545 = 0.0313744 loss) | |
| I0407 17:01:27.867908 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.359598 (* 0.0454545 = 0.0163454 loss) | |
| I0407 17:01:27.867924 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.018562 (* 0.0454545 = 0.000843727 loss) | |
| I0407 17:01:27.867939 1004 solver.cpp:245] Train net output #32: loss/loss11 = 0.00057947 (* 0.0454545 = 2.63396e-05 loss) | |
| I0407 17:01:27.867954 1004 solver.cpp:245] Train net output #33: loss/loss12 = 0.000606938 (* 0.0454545 = 2.75881e-05 loss) | |
| I0407 17:01:27.867969 1004 solver.cpp:245] Train net output #34: loss/loss13 = 0.000601852 (* 0.0454545 = 2.73569e-05 loss) | |
| I0407 17:01:27.867982 1004 solver.cpp:245] Train net output #35: loss/loss14 = 0.000603853 (* 0.0454545 = 2.74479e-05 loss) | |
| I0407 17:01:27.867996 1004 solver.cpp:245] Train net output #36: loss/loss15 = 0.000642961 (* 0.0454545 = 2.92255e-05 loss) | |
| I0407 17:01:27.868010 1004 solver.cpp:245] Train net output #37: loss/loss16 = 0.000675338 (* 0.0454545 = 3.06972e-05 loss) | |
| I0407 17:01:27.868024 1004 solver.cpp:245] Train net output #38: loss/loss17 = 0.000599987 (* 0.0454545 = 2.72721e-05 loss) | |
| I0407 17:01:27.868057 1004 solver.cpp:245] Train net output #39: loss/loss18 = 0.000635324 (* 0.0454545 = 2.88784e-05 loss) | |
| I0407 17:01:27.868072 1004 solver.cpp:245] Train net output #40: loss/loss19 = 0.000603264 (* 0.0454545 = 2.74211e-05 loss) | |
| I0407 17:01:27.868085 1004 solver.cpp:245] Train net output #41: loss/loss20 = 0.000590071 (* 0.0454545 = 2.68214e-05 loss) | |
| I0407 17:01:27.868099 1004 solver.cpp:245] Train net output #42: loss/loss21 = 0.000618556 (* 0.0454545 = 2.81162e-05 loss) | |
| I0407 17:01:27.868113 1004 solver.cpp:245] Train net output #43: loss/loss22 = 0.000620826 (* 0.0454545 = 2.82194e-05 loss) | |
| I0407 17:01:27.868125 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 17:01:27.868136 1004 solver.cpp:245] Train net output #45: total_confidence = 0.00263988 | |
| I0407 17:01:27.868151 1004 sgd_solver.cpp:106] Iteration 81000, lr = 0.000838 | |
| I0407 17:02:07.787822 1004 solver.cpp:229] Iteration 81500, loss = 0.968055 | |
| I0407 17:02:07.787961 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.0625 | |
| I0407 17:02:07.787981 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0407 17:02:07.787994 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 17:02:07.788007 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0.0625 | |
| I0407 17:02:07.788019 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.125 | |
| I0407 17:02:07.788031 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.25 | |
| I0407 17:02:07.788043 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.75 | |
| I0407 17:02:07.788054 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.9375 | |
| I0407 17:02:07.788066 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 17:02:07.788079 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 17:02:07.788090 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 17:02:07.788101 1004 solver.cpp:245] Train net output #11: loss/accuracy12 = 1 | |
| I0407 17:02:07.788112 1004 solver.cpp:245] Train net output #12: loss/accuracy13 = 1 | |
| I0407 17:02:07.788125 1004 solver.cpp:245] Train net output #13: loss/accuracy14 = 1 | |
| I0407 17:02:07.788136 1004 solver.cpp:245] Train net output #14: loss/accuracy15 = 1 | |
| I0407 17:02:07.788147 1004 solver.cpp:245] Train net output #15: loss/accuracy16 = 1 | |
| I0407 17:02:07.788158 1004 solver.cpp:245] Train net output #16: loss/accuracy17 = 1 | |
| I0407 17:02:07.788171 1004 solver.cpp:245] Train net output #17: loss/accuracy18 = 1 | |
| I0407 17:02:07.788182 1004 solver.cpp:245] Train net output #18: loss/accuracy19 = 1 | |
| I0407 17:02:07.788192 1004 solver.cpp:245] Train net output #19: loss/accuracy20 = 1 | |
| I0407 17:02:07.788204 1004 solver.cpp:245] Train net output #20: loss/accuracy21 = 1 | |
| I0407 17:02:07.788215 1004 solver.cpp:245] Train net output #21: loss/accuracy22 = 1 | |
| I0407 17:02:07.788231 1004 solver.cpp:245] Train net output #22: loss/loss01 = 3.08409 (* 0.0454545 = 0.140186 loss) | |
| I0407 17:02:07.788245 1004 solver.cpp:245] Train net output #23: loss/loss02 = 3.16583 (* 0.0454545 = 0.143901 loss) | |
| I0407 17:02:07.788259 1004 solver.cpp:245] Train net output #24: loss/loss03 = 3.36211 (* 0.0454545 = 0.152823 loss) | |
| I0407 17:02:07.788274 1004 solver.cpp:245] Train net output #25: loss/loss04 = 3.37036 (* 0.0454545 = 0.153198 loss) | |
| I0407 17:02:07.788287 1004 solver.cpp:245] Train net output #26: loss/loss05 = 3.12678 (* 0.0454545 = 0.142127 loss) | |
| I0407 17:02:07.788300 1004 solver.cpp:245] Train net output #27: loss/loss06 = 2.77723 (* 0.0454545 = 0.126238 loss) | |
| I0407 17:02:07.788314 1004 solver.cpp:245] Train net output #28: loss/loss07 = 1.42854 (* 0.0454545 = 0.0649335 loss) | |
| I0407 17:02:07.788328 1004 solver.cpp:245] Train net output #29: loss/loss08 = 0.407094 (* 0.0454545 = 0.0185043 loss) | |
| I0407 17:02:07.788342 1004 solver.cpp:245] Train net output #30: loss/loss09 = 0.361174 (* 0.0454545 = 0.016417 loss) | |
| I0407 17:02:07.788355 1004 solver.cpp:245] Train net output #31: loss/loss10 = 0.399589 (* 0.0454545 = 0.0181632 loss) | |
| I0407 17:02:07.788370 1004 solver.cpp:245] Train net output #32: loss/loss11 = 4.84288e-07 (* 0.0454545 = 2.20131e-08 loss) | |
| I0407 17:02:07.788384 1004 solver.cpp:245] Train net output #33: loss/loss12 = 5.58794e-07 (* 0.0454545 = 2.53997e-08 loss) | |
| I0407 17:02:07.788398 1004 solver.cpp:245] Train net output #34: loss/loss13 = 4.69387e-07 (* 0.0454545 = 2.13358e-08 loss) | |
| I0407 17:02:07.788411 1004 solver.cpp:245] Train net output #35: loss/loss14 = 3.42727e-07 (* 0.0454545 = 1.55785e-08 loss) | |
| I0407 17:02:07.788425 1004 solver.cpp:245] Train net output #36: loss/loss15 = 3.50178e-07 (* 0.0454545 = 1.59172e-08 loss) | |
| I0407 17:02:07.788439 1004 solver.cpp:245] Train net output #37: loss/loss16 = 4.02332e-07 (* 0.0454545 = 1.82878e-08 loss) | |
| I0407 17:02:07.788453 1004 solver.cpp:245] Train net output #38: loss/loss17 = 3.65079e-07 (* 0.0454545 = 1.65945e-08 loss) | |
| I0407 17:02:07.788480 1004 solver.cpp:245] Train net output #39: loss/loss18 = 3.27826e-07 (* 0.0454545 = 1.49012e-08 loss) | |
| I0407 17:02:07.788496 1004 solver.cpp:245] Train net output #40: loss/loss19 = 3.35276e-07 (* 0.0454545 = 1.52398e-08 loss) | |
| I0407 17:02:07.788511 1004 solver.cpp:245] Train net output #41: loss/loss20 = 3.05474e-07 (* 0.0454545 = 1.38852e-08 loss) | |
| I0407 17:02:07.788524 1004 solver.cpp:245] Train net output #42: loss/loss21 = 2.83122e-07 (* 0.0454545 = 1.28692e-08 loss) | |
| I0407 17:02:07.788537 1004 solver.cpp:245] Train net output #43: loss/loss22 = 3.7998e-07 (* 0.0454545 = 1.72718e-08 loss) | |
| I0407 17:02:07.788549 1004 solver.cpp:245] Train net output #44: total_accuracy = 0 | |
| I0407 17:02:07.788561 1004 solver.cpp:245] Train net output #45: total_confidence = 8.42924e-06 | |
| I0407 17:02:07.788574 1004 sgd_solver.cpp:106] Iteration 81500, lr = 0.000837 | |
| I0407 17:02:47.522557 1004 solver.cpp:229] Iteration 82000, loss = 0.964636 | |
| I0407 17:02:47.522671 1004 solver.cpp:245] Train net output #0: loss/accuracy01 = 0.125 | |
| I0407 17:02:47.522691 1004 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.0625 | |
| I0407 17:02:47.522704 1004 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0407 17:02:47.522716 1004 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0407 17:02:47.522728 1004 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.0625 | |
| I0407 17:02:47.522740 1004 solver.cpp:245] Train net output #5: loss/accuracy06 = 0.375 | |
| I0407 17:02:47.522752 1004 solver.cpp:245] Train net output #6: loss/accuracy07 = 0.8125 | |
| I0407 17:02:47.522763 1004 solver.cpp:245] Train net output #7: loss/accuracy08 = 0.875 | |
| I0407 17:02:47.522776 1004 solver.cpp:245] Train net output #8: loss/accuracy09 = 0.9375 | |
| I0407 17:02:47.522789 1004 solver.cpp:245] Train net output #9: loss/accuracy10 = 0.9375 | |
| I0407 17:02:47.522799 1004 solver.cpp:245] Train net output #10: loss/accuracy11 = 1 | |
| I0407 17:02:47.522814 |
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