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| I0331 10:11:54.822957 29371 solver.cpp:280] Solving mixed_lstm | |
| I0331 10:11:54.822969 29371 solver.cpp:281] Learning Rate Policy: fixed | |
| I0331 10:11:55.173683 29371 solver.cpp:229] Iteration 0, loss = 13.7452 | |
| I0331 10:11:55.173739 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0 | |
| I0331 10:11:55.173756 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0 | |
| I0331 10:11:55.173769 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.0217391 | |
| I0331 10:11:55.173785 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 4.35526 (* 0.3 = 1.30658 loss) | |
| I0331 10:11:55.173800 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 4.39893 (* 0.3 = 1.31968 loss) | |
| I0331 10:11:55.173812 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0 | |
| I0331 10:11:55.173825 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0 | |
| I0331 10:11:55.173861 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.0217391 | |
| I0331 10:11:55.173877 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 4.26857 (* 0.3 = 1.28057 loss) | |
| I0331 10:11:55.173892 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 4.49503 (* 0.3 = 1.34851 loss) | |
| I0331 10:11:55.173903 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0 | |
| I0331 10:11:55.173915 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.0625 | |
| I0331 10:11:55.173928 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0 | |
| I0331 10:11:55.173941 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 4.37604 (* 1 = 4.37604 loss) | |
| I0331 10:11:55.173954 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 4.11383 (* 1 = 4.11383 loss) | |
| I0331 10:11:55.173974 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 10:11:55.173985 29371 solver.cpp:245] Train net output #16: total_confidence = 1.74006e-35 | |
| I0331 10:11:55.174007 29371 sgd_solver.cpp:106] Iteration 0, lr = 0.005 | |
| I0331 10:11:55.191337 29371 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 40.5927 > 30) by scale factor 0.73905 | |
| I0331 10:11:55.470224 29371 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 39.5023 > 30) by scale factor 0.759449 | |
| I0331 10:11:55.734731 29371 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 41.3474 > 30) by scale factor 0.725559 | |
| I0331 10:11:55.995108 29371 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 36.3043 > 30) by scale factor 0.826349 | |
| I0331 10:11:56.256428 29371 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 35.2955 > 30) by scale factor 0.849967 | |
| I0331 10:11:56.773097 29371 sgd_solver.cpp:92] Gradient clipping: scaling down gradients (L2 norm 30.9924 > 30) by scale factor 0.967979 | |
| I0331 10:14:04.634908 29371 solver.cpp:229] Iteration 500, loss = 8.88836 | |
| I0331 10:14:04.635278 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0 | |
| I0331 10:14:04.635308 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.75 | |
| I0331 10:14:04.635332 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.113636 | |
| I0331 10:14:04.635360 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 4.08394 (* 0.3 = 1.22518 loss) | |
| I0331 10:14:04.635386 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.60149 (* 0.3 = 0.480448 loss) | |
| I0331 10:14:04.635411 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0 | |
| I0331 10:14:04.635433 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.75 | |
| I0331 10:14:04.635459 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.0909091 | |
| I0331 10:14:04.635485 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 4.11438 (* 0.3 = 1.23431 loss) | |
| I0331 10:14:04.635512 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.40173 (* 0.3 = 0.420521 loss) | |
| I0331 10:14:04.635543 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.0681818 | |
| I0331 10:14:04.635565 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.738636 | |
| I0331 10:14:04.635586 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.0909091 | |
| I0331 10:14:04.635610 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.7923 (* 1 = 3.7923 loss) | |
| I0331 10:14:04.635637 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 1.16224 (* 1 = 1.16224 loss) | |
| I0331 10:14:04.635658 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 10:14:04.635678 29371 solver.cpp:245] Train net output #16: total_confidence = 2.35854e-07 | |
| I0331 10:14:04.635699 29371 sgd_solver.cpp:106] Iteration 500, lr = 0.005 | |
| I0331 10:16:13.984201 29371 solver.cpp:229] Iteration 1000, loss = 8.02997 | |
| I0331 10:16:13.984338 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0 | |
| I0331 10:16:13.984359 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.772727 | |
| I0331 10:16:13.984380 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.075 | |
| I0331 10:16:13.984396 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.95025 (* 0.3 = 1.18508 loss) | |
| I0331 10:16:13.984411 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.25821 (* 0.3 = 0.377464 loss) | |
| I0331 10:16:13.984423 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.025 | |
| I0331 10:16:13.984436 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.778409 | |
| I0331 10:16:13.984447 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.125 | |
| I0331 10:16:13.984460 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.8443 (* 0.3 = 1.15329 loss) | |
| I0331 10:16:13.984474 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.2145 (* 0.3 = 0.36435 loss) | |
| I0331 10:16:13.984486 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.075 | |
| I0331 10:16:13.984498 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.778409 | |
| I0331 10:16:13.984510 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.2 | |
| I0331 10:16:13.984524 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.49915 (* 1 = 3.49915 loss) | |
| I0331 10:16:13.984537 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.930087 (* 1 = 0.930087 loss) | |
| I0331 10:16:13.984549 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 10:16:13.984561 29371 solver.cpp:245] Train net output #16: total_confidence = 1.0362e-05 | |
| I0331 10:16:13.984573 29371 sgd_solver.cpp:106] Iteration 1000, lr = 0.005 | |
| I0331 10:18:23.289726 29371 solver.cpp:229] Iteration 1500, loss = 7.693 | |
| I0331 10:18:23.289849 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0232558 | |
| I0331 10:18:23.289867 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.761364 | |
| I0331 10:18:23.289880 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.116279 | |
| I0331 10:18:23.289896 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 4.11007 (* 0.3 = 1.23302 loss) | |
| I0331 10:18:23.289911 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.18658 (* 0.3 = 0.355974 loss) | |
| I0331 10:18:23.289923 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0465116 | |
| I0331 10:18:23.289935 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.767045 | |
| I0331 10:18:23.289947 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.186047 | |
| I0331 10:18:23.289960 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.95413 (* 0.3 = 1.18624 loss) | |
| I0331 10:18:23.289974 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.08103 (* 0.3 = 0.32431 loss) | |
| I0331 10:18:23.289986 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.0465116 | |
| I0331 10:18:23.289999 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.744318 | |
| I0331 10:18:23.290010 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.162791 | |
| I0331 10:18:23.290024 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.7655 (* 1 = 3.7655 loss) | |
| I0331 10:18:23.290037 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 1.04576 (* 1 = 1.04576 loss) | |
| I0331 10:18:23.290048 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 10:18:23.290060 29371 solver.cpp:245] Train net output #16: total_confidence = 1.44522e-06 | |
| I0331 10:18:23.290072 29371 sgd_solver.cpp:106] Iteration 1500, lr = 0.005 | |
| I0331 10:20:32.550717 29371 solver.cpp:229] Iteration 2000, loss = 7.52533 | |
| I0331 10:20:32.550849 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0232558 | |
| I0331 10:20:32.550870 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.761364 | |
| I0331 10:20:32.550884 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.162791 | |
| I0331 10:20:32.550899 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.72586 (* 0.3 = 1.11776 loss) | |
| I0331 10:20:32.550914 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.04487 (* 0.3 = 0.313462 loss) | |
| I0331 10:20:32.550925 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0 | |
| I0331 10:20:32.550937 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.755682 | |
| I0331 10:20:32.550950 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.0930233 | |
| I0331 10:20:32.550963 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.69437 (* 0.3 = 1.10831 loss) | |
| I0331 10:20:32.550976 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.11525 (* 0.3 = 0.334575 loss) | |
| I0331 10:20:32.550988 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.139535 | |
| I0331 10:20:32.551000 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.778409 | |
| I0331 10:20:32.551012 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.255814 | |
| I0331 10:20:32.551025 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.42807 (* 1 = 3.42807 loss) | |
| I0331 10:20:32.551039 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.95957 (* 1 = 0.95957 loss) | |
| I0331 10:20:32.551051 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 10:20:32.551062 29371 solver.cpp:245] Train net output #16: total_confidence = 1.97138e-05 | |
| I0331 10:20:32.551074 29371 sgd_solver.cpp:106] Iteration 2000, lr = 0.005 | |
| I0331 10:22:41.874975 29371 solver.cpp:229] Iteration 2500, loss = 7.4327 | |
| I0331 10:22:41.875097 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0277778 | |
| I0331 10:22:41.875118 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.772727 | |
| I0331 10:22:41.875129 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.194444 | |
| I0331 10:22:41.875144 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.79261 (* 0.3 = 1.13778 loss) | |
| I0331 10:22:41.875159 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.06754 (* 0.3 = 0.320262 loss) | |
| I0331 10:22:41.875171 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0555556 | |
| I0331 10:22:41.875185 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.767045 | |
| I0331 10:22:41.875196 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.166667 | |
| I0331 10:22:41.875210 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.87865 (* 0.3 = 1.1636 loss) | |
| I0331 10:22:41.875236 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.09747 (* 0.3 = 0.329241 loss) | |
| I0331 10:22:41.875249 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.0555556 | |
| I0331 10:22:41.875262 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.761364 | |
| I0331 10:22:41.875273 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.194444 | |
| I0331 10:22:41.875286 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.29159 (* 1 = 3.29159 loss) | |
| I0331 10:22:41.875300 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.920495 (* 1 = 0.920495 loss) | |
| I0331 10:22:41.875313 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 10:22:41.875324 29371 solver.cpp:245] Train net output #16: total_confidence = 1.08607e-05 | |
| I0331 10:22:41.875335 29371 sgd_solver.cpp:106] Iteration 2500, lr = 0.005 | |
| I0331 10:24:51.110877 29371 solver.cpp:229] Iteration 3000, loss = 7.31331 | |
| I0331 10:24:51.111007 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0217391 | |
| I0331 10:24:51.111026 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.744318 | |
| I0331 10:24:51.111038 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.130435 | |
| I0331 10:24:51.111063 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.99443 (* 0.3 = 1.19833 loss) | |
| I0331 10:24:51.111076 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.16851 (* 0.3 = 0.350552 loss) | |
| I0331 10:24:51.111089 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0652174 | |
| I0331 10:24:51.111101 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.755682 | |
| I0331 10:24:51.111112 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.152174 | |
| I0331 10:24:51.111138 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 4.12463 (* 0.3 = 1.23739 loss) | |
| I0331 10:24:51.111155 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.19478 (* 0.3 = 0.358433 loss) | |
| I0331 10:24:51.111167 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.0217391 | |
| I0331 10:24:51.111179 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.738636 | |
| I0331 10:24:51.111191 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.195652 | |
| I0331 10:24:51.111204 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.93893 (* 1 = 3.93893 loss) | |
| I0331 10:24:51.111217 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 1.08926 (* 1 = 1.08926 loss) | |
| I0331 10:24:51.111229 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 10:24:51.111240 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000390162 | |
| I0331 10:24:51.111253 29371 sgd_solver.cpp:106] Iteration 3000, lr = 0.005 | |
| I0331 10:27:00.330831 29371 solver.cpp:229] Iteration 3500, loss = 7.23063 | |
| I0331 10:27:00.330986 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0526316 | |
| I0331 10:27:00.331006 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.789773 | |
| I0331 10:27:00.331019 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.157895 | |
| I0331 10:27:00.331037 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.54758 (* 0.3 = 1.06427 loss) | |
| I0331 10:27:00.331050 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.04461 (* 0.3 = 0.313382 loss) | |
| I0331 10:27:00.331063 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0263158 | |
| I0331 10:27:00.331074 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.778409 | |
| I0331 10:27:00.331110 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.131579 | |
| I0331 10:27:00.331127 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.61339 (* 0.3 = 1.08402 loss) | |
| I0331 10:27:00.331141 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.910106 (* 0.3 = 0.273032 loss) | |
| I0331 10:27:00.331154 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.0526316 | |
| I0331 10:27:00.331166 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.761364 | |
| I0331 10:27:00.331179 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.157895 | |
| I0331 10:27:00.331193 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.38577 (* 1 = 3.38577 loss) | |
| I0331 10:27:00.331207 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.97128 (* 1 = 0.97128 loss) | |
| I0331 10:27:00.331219 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 10:27:00.331231 29371 solver.cpp:245] Train net output #16: total_confidence = 3.77281e-06 | |
| I0331 10:27:00.331244 29371 sgd_solver.cpp:106] Iteration 3500, lr = 0.005 | |
| I0331 10:29:09.724510 29371 solver.cpp:229] Iteration 4000, loss = 7.15319 | |
| I0331 10:29:09.724674 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0888889 | |
| I0331 10:29:09.724695 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.744318 | |
| I0331 10:29:09.724709 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.177778 | |
| I0331 10:29:09.724728 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.39427 (* 0.3 = 1.01828 loss) | |
| I0331 10:29:09.724743 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.0609 (* 0.3 = 0.318272 loss) | |
| I0331 10:29:09.724756 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0666667 | |
| I0331 10:29:09.724768 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.738636 | |
| I0331 10:29:09.724779 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.155556 | |
| I0331 10:29:09.724793 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.35826 (* 0.3 = 1.00748 loss) | |
| I0331 10:29:09.724807 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.02936 (* 0.3 = 0.308809 loss) | |
| I0331 10:29:09.724818 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.0444444 | |
| I0331 10:29:09.724831 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.755682 | |
| I0331 10:29:09.724843 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.2 | |
| I0331 10:29:09.724856 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.18783 (* 1 = 3.18783 loss) | |
| I0331 10:29:09.724870 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.897842 (* 1 = 0.897842 loss) | |
| I0331 10:29:09.724882 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 10:29:09.724895 29371 solver.cpp:245] Train net output #16: total_confidence = 4.79103e-06 | |
| I0331 10:29:09.724907 29371 sgd_solver.cpp:106] Iteration 4000, lr = 0.005 | |
| I0331 10:31:18.922924 29371 solver.cpp:229] Iteration 4500, loss = 7.11114 | |
| I0331 10:31:18.923033 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0816327 | |
| I0331 10:31:18.923053 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.698864 | |
| I0331 10:31:18.923065 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.22449 | |
| I0331 10:31:18.923082 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.26065 (* 0.3 = 0.978196 loss) | |
| I0331 10:31:18.923100 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.17328 (* 0.3 = 0.351984 loss) | |
| I0331 10:31:18.923113 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0816327 | |
| I0331 10:31:18.923126 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.732955 | |
| I0331 10:31:18.923138 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.265306 | |
| I0331 10:31:18.923151 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.2895 (* 0.3 = 0.986849 loss) | |
| I0331 10:31:18.923179 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.11202 (* 0.3 = 0.333607 loss) | |
| I0331 10:31:18.923192 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.102041 | |
| I0331 10:31:18.923205 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.75 | |
| I0331 10:31:18.923223 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.285714 | |
| I0331 10:31:18.923235 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.0201 (* 1 = 3.0201 loss) | |
| I0331 10:31:18.923249 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.929249 (* 1 = 0.929249 loss) | |
| I0331 10:31:18.923261 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 10:31:18.923280 29371 solver.cpp:245] Train net output #16: total_confidence = 2.40988e-05 | |
| I0331 10:31:18.923291 29371 sgd_solver.cpp:106] Iteration 4500, lr = 0.005 | |
| I0331 10:33:28.079797 29371 solver.cpp:338] Iteration 5000, Testing net (#0) | |
| I0331 10:33:57.943186 29371 solver.cpp:393] Test loss: 6.7187 | |
| I0331 10:33:57.943243 29371 solver.cpp:406] Test net output #0: loss1/accuracy = 0.0826361 | |
| I0331 10:33:57.943260 29371 solver.cpp:406] Test net output #1: loss1/accuracy_incl_empty = 0.776182 | |
| I0331 10:33:57.943272 29371 solver.cpp:406] Test net output #2: loss1/accuracy_top3 = 0.245423 | |
| I0331 10:33:57.943289 29371 solver.cpp:406] Test net output #3: loss1/cross_entropy_loss = 4.3204 (* 0.3 = 1.29612 loss) | |
| I0331 10:33:57.943302 29371 solver.cpp:406] Test net output #4: loss1/cross_entropy_loss_incl_empty = 1.08667 (* 0.3 = 0.326 loss) | |
| I0331 10:33:57.943315 29371 solver.cpp:406] Test net output #5: loss2/accuracy = 0.104623 | |
| I0331 10:33:57.943327 29371 solver.cpp:406] Test net output #6: loss2/accuracy_incl_empty = 0.780363 | |
| I0331 10:33:57.943339 29371 solver.cpp:406] Test net output #7: loss2/accuracy_top3 = 0.284835 | |
| I0331 10:33:57.943352 29371 solver.cpp:406] Test net output #8: loss2/cross_entropy_loss = 3.56291 (* 0.3 = 1.06887 loss) | |
| I0331 10:33:57.943367 29371 solver.cpp:406] Test net output #9: loss2/cross_entropy_loss_incl_empty = 0.892749 (* 0.3 = 0.267825 loss) | |
| I0331 10:33:57.943378 29371 solver.cpp:406] Test net output #10: loss3/accuracy = 0.103399 | |
| I0331 10:33:57.943390 29371 solver.cpp:406] Test net output #11: loss3/accuracy_incl_empty = 0.77409 | |
| I0331 10:33:57.943403 29371 solver.cpp:406] Test net output #12: loss3/accuracy_top3 = 0.297888 | |
| I0331 10:33:57.943415 29371 solver.cpp:406] Test net output #13: loss3/cross_entropy_loss = 2.96033 (* 1 = 2.96033 loss) | |
| I0331 10:33:57.943428 29371 solver.cpp:406] Test net output #14: loss3/cross_entropy_loss_incl_empty = 0.799546 (* 1 = 0.799546 loss) | |
| I0331 10:33:57.943440 29371 solver.cpp:406] Test net output #15: total_accuracy = 0.001 | |
| I0331 10:33:57.943452 29371 solver.cpp:406] Test net output #16: total_confidence = 0.000117102 | |
| I0331 10:33:58.094144 29371 solver.cpp:229] Iteration 5000, loss = 7.04981 | |
| I0331 10:33:58.094254 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0833333 | |
| I0331 10:33:58.094274 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.715909 | |
| I0331 10:33:58.094287 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.270833 | |
| I0331 10:33:58.094302 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.18465 (* 0.3 = 0.955395 loss) | |
| I0331 10:33:58.094316 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.17613 (* 0.3 = 0.352839 loss) | |
| I0331 10:33:58.094329 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0625 | |
| I0331 10:33:58.094341 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.744318 | |
| I0331 10:33:58.094353 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.145833 | |
| I0331 10:33:58.094367 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.24585 (* 0.3 = 0.973756 loss) | |
| I0331 10:33:58.094380 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.963131 (* 0.3 = 0.288939 loss) | |
| I0331 10:33:58.094393 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.125 | |
| I0331 10:33:58.094404 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.761364 | |
| I0331 10:33:58.094416 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.25 | |
| I0331 10:33:58.094430 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.08983 (* 1 = 3.08983 loss) | |
| I0331 10:33:58.094444 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.904983 (* 1 = 0.904983 loss) | |
| I0331 10:33:58.094456 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 10:33:58.094467 29371 solver.cpp:245] Train net output #16: total_confidence = 2.90156e-05 | |
| I0331 10:33:58.094480 29371 sgd_solver.cpp:106] Iteration 5000, lr = 0.005 | |
| I0331 10:36:07.409035 29371 solver.cpp:229] Iteration 5500, loss = 7.01439 | |
| I0331 10:36:07.409169 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0204082 | |
| I0331 10:36:07.409189 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.727273 | |
| I0331 10:36:07.409201 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.122449 | |
| I0331 10:36:07.409219 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.95194 (* 0.3 = 1.18558 loss) | |
| I0331 10:36:07.409234 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.25419 (* 0.3 = 0.376258 loss) | |
| I0331 10:36:07.409245 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0204082 | |
| I0331 10:36:07.409257 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.727273 | |
| I0331 10:36:07.409268 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.0612245 | |
| I0331 10:36:07.409282 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 4.10045 (* 0.3 = 1.23013 loss) | |
| I0331 10:36:07.409296 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.26425 (* 0.3 = 0.379275 loss) | |
| I0331 10:36:07.409307 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.0408163 | |
| I0331 10:36:07.409320 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.727273 | |
| I0331 10:36:07.409332 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.102041 | |
| I0331 10:36:07.409346 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 4.01884 (* 1 = 4.01884 loss) | |
| I0331 10:36:07.409360 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 1.23177 (* 1 = 1.23177 loss) | |
| I0331 10:36:07.409373 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 10:36:07.409384 29371 solver.cpp:245] Train net output #16: total_confidence = 0.00010573 | |
| I0331 10:36:07.409395 29371 sgd_solver.cpp:106] Iteration 5500, lr = 0.005 | |
| I0331 10:38:16.717413 29371 solver.cpp:229] Iteration 6000, loss = 7.02953 | |
| I0331 10:38:16.717535 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0625 | |
| I0331 10:38:16.717555 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.744318 | |
| I0331 10:38:16.717568 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.208333 | |
| I0331 10:38:16.717584 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.37843 (* 0.3 = 1.01353 loss) | |
| I0331 10:38:16.717599 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.985016 (* 0.3 = 0.295505 loss) | |
| I0331 10:38:16.717612 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0833333 | |
| I0331 10:38:16.717623 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.75 | |
| I0331 10:38:16.717635 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.229167 | |
| I0331 10:38:16.717649 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.2813 (* 0.3 = 0.98439 loss) | |
| I0331 10:38:16.717664 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.995757 (* 0.3 = 0.298727 loss) | |
| I0331 10:38:16.717675 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.0833333 | |
| I0331 10:38:16.717687 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.75 | |
| I0331 10:38:16.717700 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.1875 | |
| I0331 10:38:16.717713 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.24508 (* 1 = 3.24508 loss) | |
| I0331 10:38:16.717727 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.943073 (* 1 = 0.943073 loss) | |
| I0331 10:38:16.717739 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 10:38:16.717751 29371 solver.cpp:245] Train net output #16: total_confidence = 1.349e-06 | |
| I0331 10:38:16.717762 29371 sgd_solver.cpp:106] Iteration 6000, lr = 0.005 | |
| I0331 10:40:25.936784 29371 solver.cpp:229] Iteration 6500, loss = 6.96014 | |
| I0331 10:40:25.936947 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0727273 | |
| I0331 10:40:25.936974 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.704545 | |
| I0331 10:40:25.936986 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.272727 | |
| I0331 10:40:25.937002 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.25086 (* 0.3 = 0.975257 loss) | |
| I0331 10:40:25.937017 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.08928 (* 0.3 = 0.326783 loss) | |
| I0331 10:40:25.937031 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0909091 | |
| I0331 10:40:25.937042 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.710227 | |
| I0331 10:40:25.937054 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.236364 | |
| I0331 10:40:25.937068 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.18615 (* 0.3 = 0.955845 loss) | |
| I0331 10:40:25.937085 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.15237 (* 0.3 = 0.345711 loss) | |
| I0331 10:40:25.937103 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.0727273 | |
| I0331 10:40:25.937125 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.710227 | |
| I0331 10:40:25.937137 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.2 | |
| I0331 10:40:25.937151 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.22716 (* 1 = 3.22716 loss) | |
| I0331 10:40:25.937165 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 1.03092 (* 1 = 1.03092 loss) | |
| I0331 10:40:25.937186 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 10:40:25.937197 29371 solver.cpp:245] Train net output #16: total_confidence = 1.47977e-05 | |
| I0331 10:40:25.937209 29371 sgd_solver.cpp:106] Iteration 6500, lr = 0.005 | |
| I0331 10:42:35.044544 29371 solver.cpp:229] Iteration 7000, loss = 6.91925 | |
| I0331 10:42:35.044667 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0408163 | |
| I0331 10:42:35.044688 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.732955 | |
| I0331 10:42:35.044702 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.204082 | |
| I0331 10:42:35.044720 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.28497 (* 0.3 = 0.98549 loss) | |
| I0331 10:42:35.044749 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.99096 (* 0.3 = 0.297288 loss) | |
| I0331 10:42:35.044766 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0816327 | |
| I0331 10:42:35.044780 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.744318 | |
| I0331 10:42:35.044791 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.204082 | |
| I0331 10:42:35.044806 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.22523 (* 0.3 = 0.967569 loss) | |
| I0331 10:42:35.044819 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.0295 (* 0.3 = 0.30885 loss) | |
| I0331 10:42:35.044839 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.0816327 | |
| I0331 10:42:35.044852 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.744318 | |
| I0331 10:42:35.044863 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.204082 | |
| I0331 10:42:35.044878 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.10647 (* 1 = 3.10647 loss) | |
| I0331 10:42:35.044899 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.930912 (* 1 = 0.930912 loss) | |
| I0331 10:42:35.044910 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 10:42:35.044922 29371 solver.cpp:245] Train net output #16: total_confidence = 1.03245e-06 | |
| I0331 10:42:35.044935 29371 sgd_solver.cpp:106] Iteration 7000, lr = 0.005 | |
| I0331 10:44:44.320749 29371 solver.cpp:229] Iteration 7500, loss = 6.88459 | |
| I0331 10:44:44.320874 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0444444 | |
| I0331 10:44:44.320894 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.732955 | |
| I0331 10:44:44.320906 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.2 | |
| I0331 10:44:44.320922 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.55548 (* 0.3 = 1.06664 loss) | |
| I0331 10:44:44.320942 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.1354 (* 0.3 = 0.340619 loss) | |
| I0331 10:44:44.320955 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0666667 | |
| I0331 10:44:44.320967 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.738636 | |
| I0331 10:44:44.320979 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.133333 | |
| I0331 10:44:44.320993 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.64615 (* 0.3 = 1.09385 loss) | |
| I0331 10:44:44.321007 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.12334 (* 0.3 = 0.337002 loss) | |
| I0331 10:44:44.321020 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.0666667 | |
| I0331 10:44:44.321033 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.744318 | |
| I0331 10:44:44.321044 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.2 | |
| I0331 10:44:44.321066 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.64231 (* 1 = 3.64231 loss) | |
| I0331 10:44:44.321082 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 1.08986 (* 1 = 1.08986 loss) | |
| I0331 10:44:44.321095 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 10:44:44.321108 29371 solver.cpp:245] Train net output #16: total_confidence = 9.749e-07 | |
| I0331 10:44:44.321135 29371 sgd_solver.cpp:106] Iteration 7500, lr = 0.005 | |
| I0331 10:46:53.639705 29371 solver.cpp:229] Iteration 8000, loss = 6.83412 | |
| I0331 10:46:53.639816 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0625 | |
| I0331 10:46:53.639834 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.738636 | |
| I0331 10:46:53.639847 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.166667 | |
| I0331 10:46:53.639863 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.61377 (* 0.3 = 1.08413 loss) | |
| I0331 10:46:53.639878 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.07457 (* 0.3 = 0.322371 loss) | |
| I0331 10:46:53.639890 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0625 | |
| I0331 10:46:53.639904 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.744318 | |
| I0331 10:46:53.639915 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.145833 | |
| I0331 10:46:53.639930 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.43387 (* 0.3 = 1.03016 loss) | |
| I0331 10:46:53.639943 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.04034 (* 0.3 = 0.312103 loss) | |
| I0331 10:46:53.639955 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.0625 | |
| I0331 10:46:53.639968 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.738636 | |
| I0331 10:46:53.639979 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.229167 | |
| I0331 10:46:53.639993 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.32582 (* 1 = 3.32582 loss) | |
| I0331 10:46:53.640007 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 1.00869 (* 1 = 1.00869 loss) | |
| I0331 10:46:53.640019 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 10:46:53.640030 29371 solver.cpp:245] Train net output #16: total_confidence = 6.89496e-07 | |
| I0331 10:46:53.640043 29371 sgd_solver.cpp:106] Iteration 8000, lr = 0.005 | |
| I0331 10:49:02.839650 29371 solver.cpp:229] Iteration 8500, loss = 6.81751 | |
| I0331 10:49:02.839810 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0909091 | |
| I0331 10:49:02.839830 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.767045 | |
| I0331 10:49:02.839844 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.181818 | |
| I0331 10:49:02.839860 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.49278 (* 0.3 = 1.04783 loss) | |
| I0331 10:49:02.839874 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.971314 (* 0.3 = 0.291394 loss) | |
| I0331 10:49:02.839887 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0454545 | |
| I0331 10:49:02.839900 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.75 | |
| I0331 10:49:02.839912 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.136364 | |
| I0331 10:49:02.839926 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.28868 (* 0.3 = 0.986604 loss) | |
| I0331 10:49:02.839941 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.997508 (* 0.3 = 0.299252 loss) | |
| I0331 10:49:02.839953 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.159091 | |
| I0331 10:49:02.839967 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.784091 | |
| I0331 10:49:02.839978 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.227273 | |
| I0331 10:49:02.839993 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.1571 (* 1 = 3.1571 loss) | |
| I0331 10:49:02.840005 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.856876 (* 1 = 0.856876 loss) | |
| I0331 10:49:02.840018 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 10:49:02.840029 29371 solver.cpp:245] Train net output #16: total_confidence = 2.94559e-05 | |
| I0331 10:49:02.840042 29371 sgd_solver.cpp:106] Iteration 8500, lr = 0.005 | |
| I0331 10:51:12.199910 29371 solver.cpp:229] Iteration 9000, loss = 6.81623 | |
| I0331 10:51:12.200037 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0408163 | |
| I0331 10:51:12.200057 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.721591 | |
| I0331 10:51:12.200070 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.163265 | |
| I0331 10:51:12.200088 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.36092 (* 0.3 = 1.00828 loss) | |
| I0331 10:51:12.200103 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.06913 (* 0.3 = 0.32074 loss) | |
| I0331 10:51:12.200116 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.102041 | |
| I0331 10:51:12.200129 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.75 | |
| I0331 10:51:12.200141 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.163265 | |
| I0331 10:51:12.200155 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.29754 (* 0.3 = 0.989261 loss) | |
| I0331 10:51:12.200170 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.00462 (* 0.3 = 0.301385 loss) | |
| I0331 10:51:12.200182 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.0612245 | |
| I0331 10:51:12.200194 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.738636 | |
| I0331 10:51:12.200206 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.204082 | |
| I0331 10:51:12.200219 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.18989 (* 1 = 3.18989 loss) | |
| I0331 10:51:12.200233 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.917042 (* 1 = 0.917042 loss) | |
| I0331 10:51:12.200245 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 10:51:12.200258 29371 solver.cpp:245] Train net output #16: total_confidence = 1.8716e-05 | |
| I0331 10:51:12.200269 29371 sgd_solver.cpp:106] Iteration 9000, lr = 0.005 | |
| I0331 10:53:21.340693 29371 solver.cpp:229] Iteration 9500, loss = 6.85728 | |
| I0331 10:53:21.340852 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.097561 | |
| I0331 10:53:21.340883 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.772727 | |
| I0331 10:53:21.340896 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.243902 | |
| I0331 10:53:21.340912 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.17213 (* 0.3 = 0.951639 loss) | |
| I0331 10:53:21.340929 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.944764 (* 0.3 = 0.283429 loss) | |
| I0331 10:53:21.340951 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.121951 | |
| I0331 10:53:21.340966 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.784091 | |
| I0331 10:53:21.340980 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.268293 | |
| I0331 10:53:21.340993 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.12326 (* 0.3 = 0.936979 loss) | |
| I0331 10:53:21.341007 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.867427 (* 0.3 = 0.260228 loss) | |
| I0331 10:53:21.341019 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.0243902 | |
| I0331 10:53:21.341032 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.761364 | |
| I0331 10:53:21.341043 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.243902 | |
| I0331 10:53:21.341058 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.99402 (* 1 = 2.99402 loss) | |
| I0331 10:53:21.341071 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.81767 (* 1 = 0.81767 loss) | |
| I0331 10:53:21.341085 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 10:53:21.341100 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000347855 | |
| I0331 10:53:21.341122 29371 sgd_solver.cpp:106] Iteration 9500, lr = 0.005 | |
| I0331 10:55:30.364259 29371 solver.cpp:338] Iteration 10000, Testing net (#0) | |
| I0331 10:56:00.182315 29371 solver.cpp:393] Test loss: 6.21063 | |
| I0331 10:56:00.182363 29371 solver.cpp:406] Test net output #0: loss1/accuracy = 0.128677 | |
| I0331 10:56:00.182379 29371 solver.cpp:406] Test net output #1: loss1/accuracy_incl_empty = 0.785227 | |
| I0331 10:56:00.182390 29371 solver.cpp:406] Test net output #2: loss1/accuracy_top3 = 0.335342 | |
| I0331 10:56:00.182406 29371 solver.cpp:406] Test net output #3: loss1/cross_entropy_loss = 3.67625 (* 0.3 = 1.10288 loss) | |
| I0331 10:56:00.182420 29371 solver.cpp:406] Test net output #4: loss1/cross_entropy_loss_incl_empty = 0.926278 (* 0.3 = 0.277883 loss) | |
| I0331 10:56:00.182432 29371 solver.cpp:406] Test net output #5: loss2/accuracy = 0.134199 | |
| I0331 10:56:00.182445 29371 solver.cpp:406] Test net output #6: loss2/accuracy_incl_empty = 0.787136 | |
| I0331 10:56:00.182456 29371 solver.cpp:406] Test net output #7: loss2/accuracy_top3 = 0.330217 | |
| I0331 10:56:00.182469 29371 solver.cpp:406] Test net output #8: loss2/cross_entropy_loss = 3.48941 (* 0.3 = 1.04682 loss) | |
| I0331 10:56:00.182483 29371 solver.cpp:406] Test net output #9: loss2/cross_entropy_loss_incl_empty = 0.876604 (* 0.3 = 0.262981 loss) | |
| I0331 10:56:00.182495 29371 solver.cpp:406] Test net output #10: loss3/accuracy = 0.127345 | |
| I0331 10:56:00.182507 29371 solver.cpp:406] Test net output #11: loss3/accuracy_incl_empty = 0.781682 | |
| I0331 10:56:00.182518 29371 solver.cpp:406] Test net output #12: loss3/accuracy_top3 = 0.325004 | |
| I0331 10:56:00.182531 29371 solver.cpp:406] Test net output #13: loss3/cross_entropy_loss = 2.79364 (* 1 = 2.79364 loss) | |
| I0331 10:56:00.182545 29371 solver.cpp:406] Test net output #14: loss3/cross_entropy_loss_incl_empty = 0.726433 (* 1 = 0.726433 loss) | |
| I0331 10:56:00.182556 29371 solver.cpp:406] Test net output #15: total_accuracy = 0.001 | |
| I0331 10:56:00.182569 29371 solver.cpp:406] Test net output #16: total_confidence = 0.000218828 | |
| I0331 10:56:00.334219 29371 solver.cpp:229] Iteration 10000, loss = 6.79001 | |
| I0331 10:56:00.334259 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0869565 | |
| I0331 10:56:00.334276 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.755682 | |
| I0331 10:56:00.334290 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.195652 | |
| I0331 10:56:00.334305 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.30251 (* 0.3 = 0.990753 loss) | |
| I0331 10:56:00.334319 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.954561 (* 0.3 = 0.286368 loss) | |
| I0331 10:56:00.334331 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0869565 | |
| I0331 10:56:00.334345 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.75 | |
| I0331 10:56:00.334357 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.195652 | |
| I0331 10:56:00.334372 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.23312 (* 0.3 = 0.969935 loss) | |
| I0331 10:56:00.334389 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.01066 (* 0.3 = 0.303198 loss) | |
| I0331 10:56:00.334401 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.130435 | |
| I0331 10:56:00.334414 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.755682 | |
| I0331 10:56:00.334425 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.23913 | |
| I0331 10:56:00.334439 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.06273 (* 1 = 3.06273 loss) | |
| I0331 10:56:00.334453 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.935906 (* 1 = 0.935906 loss) | |
| I0331 10:56:00.334465 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 10:56:00.334477 29371 solver.cpp:245] Train net output #16: total_confidence = 2.13249e-06 | |
| I0331 10:56:00.334489 29371 sgd_solver.cpp:106] Iteration 10000, lr = 0.005 | |
| I0331 10:58:09.439512 29371 solver.cpp:229] Iteration 10500, loss = 6.7527 | |
| I0331 10:58:09.439671 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.097561 | |
| I0331 10:58:09.439692 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.772727 | |
| I0331 10:58:09.439712 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.195122 | |
| I0331 10:58:09.439733 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.30281 (* 0.3 = 0.990842 loss) | |
| I0331 10:58:09.439748 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.925296 (* 0.3 = 0.277589 loss) | |
| I0331 10:58:09.439759 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0731707 | |
| I0331 10:58:09.439772 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.767045 | |
| I0331 10:58:09.439784 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.243902 | |
| I0331 10:58:09.439797 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.22846 (* 0.3 = 0.968537 loss) | |
| I0331 10:58:09.439811 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.904582 (* 0.3 = 0.271375 loss) | |
| I0331 10:58:09.439823 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.146341 | |
| I0331 10:58:09.439836 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.784091 | |
| I0331 10:58:09.439847 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.170732 | |
| I0331 10:58:09.439862 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.09379 (* 1 = 3.09379 loss) | |
| I0331 10:58:09.439875 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.851398 (* 1 = 0.851398 loss) | |
| I0331 10:58:09.439888 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 10:58:09.439898 29371 solver.cpp:245] Train net output #16: total_confidence = 5.17733e-05 | |
| I0331 10:58:09.439911 29371 sgd_solver.cpp:106] Iteration 10500, lr = 0.005 | |
| I0331 11:00:18.731660 29371 solver.cpp:229] Iteration 11000, loss = 6.70253 | |
| I0331 11:00:18.731801 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.15 | |
| I0331 11:00:18.731822 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.778409 | |
| I0331 11:00:18.731842 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.2 | |
| I0331 11:00:18.731856 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.25866 (* 0.3 = 0.977599 loss) | |
| I0331 11:00:18.731871 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.90788 (* 0.3 = 0.272364 loss) | |
| I0331 11:00:18.731884 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.15 | |
| I0331 11:00:18.731895 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.801136 | |
| I0331 11:00:18.731907 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.25 | |
| I0331 11:00:18.731921 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.09592 (* 0.3 = 0.928777 loss) | |
| I0331 11:00:18.731935 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.816151 (* 0.3 = 0.244845 loss) | |
| I0331 11:00:18.731948 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.175 | |
| I0331 11:00:18.731961 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.801136 | |
| I0331 11:00:18.731973 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.3 | |
| I0331 11:00:18.731987 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.95703 (* 1 = 2.95703 loss) | |
| I0331 11:00:18.732000 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.777933 (* 1 = 0.777933 loss) | |
| I0331 11:00:18.732012 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:00:18.732028 29371 solver.cpp:245] Train net output #16: total_confidence = 7.88455e-05 | |
| I0331 11:00:18.732039 29371 sgd_solver.cpp:106] Iteration 11000, lr = 0.005 | |
| I0331 11:02:27.889907 29371 solver.cpp:229] Iteration 11500, loss = 6.70198 | |
| I0331 11:02:27.890039 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0392157 | |
| I0331 11:02:27.890059 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.710227 | |
| I0331 11:02:27.890071 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.196078 | |
| I0331 11:02:27.890090 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.33383 (* 0.3 = 1.00015 loss) | |
| I0331 11:02:27.890105 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.062 (* 0.3 = 0.3186 loss) | |
| I0331 11:02:27.890118 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0784314 | |
| I0331 11:02:27.890130 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.732955 | |
| I0331 11:02:27.890142 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.196078 | |
| I0331 11:02:27.890156 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.12421 (* 0.3 = 0.937264 loss) | |
| I0331 11:02:27.890171 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.981691 (* 0.3 = 0.294507 loss) | |
| I0331 11:02:27.890182 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.0588235 | |
| I0331 11:02:27.890194 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.715909 | |
| I0331 11:02:27.890208 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.176471 | |
| I0331 11:02:27.890221 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.14975 (* 1 = 3.14975 loss) | |
| I0331 11:02:27.890234 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.99047 (* 1 = 0.99047 loss) | |
| I0331 11:02:27.890246 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:02:27.890259 29371 solver.cpp:245] Train net output #16: total_confidence = 9.42174e-07 | |
| I0331 11:02:27.890278 29371 sgd_solver.cpp:106] Iteration 11500, lr = 0.005 | |
| I0331 11:04:37.039273 29371 solver.cpp:229] Iteration 12000, loss = 6.66236 | |
| I0331 11:04:37.039433 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.06 | |
| I0331 11:04:37.039455 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.727273 | |
| I0331 11:04:37.039469 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.2 | |
| I0331 11:04:37.039484 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.43726 (* 0.3 = 1.03118 loss) | |
| I0331 11:04:37.039499 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.0345 (* 0.3 = 0.31035 loss) | |
| I0331 11:04:37.039511 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.08 | |
| I0331 11:04:37.039525 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.732955 | |
| I0331 11:04:37.039536 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.28 | |
| I0331 11:04:37.039551 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.38264 (* 0.3 = 1.01479 loss) | |
| I0331 11:04:37.039564 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.04615 (* 0.3 = 0.313845 loss) | |
| I0331 11:04:37.039577 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.14 | |
| I0331 11:04:37.039589 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.75 | |
| I0331 11:04:37.039602 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.24 | |
| I0331 11:04:37.039615 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.18246 (* 1 = 3.18246 loss) | |
| I0331 11:04:37.039629 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.94441 (* 1 = 0.94441 loss) | |
| I0331 11:04:37.039641 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:04:37.039654 29371 solver.cpp:245] Train net output #16: total_confidence = 1.85191e-05 | |
| I0331 11:04:37.039666 29371 sgd_solver.cpp:106] Iteration 12000, lr = 0.005 | |
| I0331 11:06:46.445688 29371 solver.cpp:229] Iteration 12500, loss = 6.6551 | |
| I0331 11:06:46.445806 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.025641 | |
| I0331 11:06:46.445825 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.772727 | |
| I0331 11:06:46.445838 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.230769 | |
| I0331 11:06:46.445854 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.23485 (* 0.3 = 0.970456 loss) | |
| I0331 11:06:46.445869 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.866016 (* 0.3 = 0.259805 loss) | |
| I0331 11:06:46.445881 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0769231 | |
| I0331 11:06:46.445894 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.789773 | |
| I0331 11:06:46.445906 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.153846 | |
| I0331 11:06:46.445919 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.27191 (* 0.3 = 0.981574 loss) | |
| I0331 11:06:46.445933 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.82112 (* 0.3 = 0.246336 loss) | |
| I0331 11:06:46.445945 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.0512821 | |
| I0331 11:06:46.445957 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.784091 | |
| I0331 11:06:46.445969 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.179487 | |
| I0331 11:06:46.445982 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.344 (* 1 = 3.344 loss) | |
| I0331 11:06:46.445996 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.837673 (* 1 = 0.837673 loss) | |
| I0331 11:06:46.446008 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:06:46.446020 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000845842 | |
| I0331 11:06:46.446033 29371 sgd_solver.cpp:106] Iteration 12500, lr = 0.005 | |
| I0331 11:08:55.742089 29371 solver.cpp:229] Iteration 13000, loss = 6.65604 | |
| I0331 11:08:55.742221 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0930233 | |
| I0331 11:08:55.742241 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.772727 | |
| I0331 11:08:55.742254 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.27907 | |
| I0331 11:08:55.742269 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.05957 (* 0.3 = 0.91787 loss) | |
| I0331 11:08:55.742285 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.859095 (* 0.3 = 0.257729 loss) | |
| I0331 11:08:55.742296 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.162791 | |
| I0331 11:08:55.742312 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.778409 | |
| I0331 11:08:55.742324 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.348837 | |
| I0331 11:08:55.742337 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.9947 (* 0.3 = 0.898411 loss) | |
| I0331 11:08:55.742352 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.890718 (* 0.3 = 0.267215 loss) | |
| I0331 11:08:55.742363 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.139535 | |
| I0331 11:08:55.742375 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.767045 | |
| I0331 11:08:55.742393 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.302326 | |
| I0331 11:08:55.742408 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.89083 (* 1 = 2.89083 loss) | |
| I0331 11:08:55.742422 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.848455 (* 1 = 0.848455 loss) | |
| I0331 11:08:55.742439 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:08:55.742458 29371 solver.cpp:245] Train net output #16: total_confidence = 4.98174e-06 | |
| I0331 11:08:55.742472 29371 sgd_solver.cpp:106] Iteration 13000, lr = 0.005 | |
| I0331 11:11:04.714826 29371 solver.cpp:229] Iteration 13500, loss = 6.60027 | |
| I0331 11:11:04.714963 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.04 | |
| I0331 11:11:04.714983 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.727273 | |
| I0331 11:11:04.714997 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.1 | |
| I0331 11:11:04.715013 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.54095 (* 0.3 = 1.06228 loss) | |
| I0331 11:11:04.715028 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.05427 (* 0.3 = 0.31628 loss) | |
| I0331 11:11:04.715039 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.06 | |
| I0331 11:11:04.715050 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.727273 | |
| I0331 11:11:04.715062 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.18 | |
| I0331 11:11:04.715076 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.38635 (* 0.3 = 1.01591 loss) | |
| I0331 11:11:04.715108 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.0811 (* 0.3 = 0.324331 loss) | |
| I0331 11:11:04.715121 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.06 | |
| I0331 11:11:04.715134 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.721591 | |
| I0331 11:11:04.715145 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.16 | |
| I0331 11:11:04.715159 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.4508 (* 1 = 3.4508 loss) | |
| I0331 11:11:04.715173 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 1.05537 (* 1 = 1.05537 loss) | |
| I0331 11:11:04.715183 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:11:04.715195 29371 solver.cpp:245] Train net output #16: total_confidence = 8.1446e-05 | |
| I0331 11:11:04.715207 29371 sgd_solver.cpp:106] Iteration 13500, lr = 0.005 | |
| I0331 11:13:13.897949 29371 solver.cpp:229] Iteration 14000, loss = 6.58724 | |
| I0331 11:13:13.898285 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0392157 | |
| I0331 11:13:13.898308 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.715909 | |
| I0331 11:13:13.898320 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.176471 | |
| I0331 11:13:13.898336 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.45695 (* 0.3 = 1.03708 loss) | |
| I0331 11:13:13.898350 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.07358 (* 0.3 = 0.322073 loss) | |
| I0331 11:13:13.898363 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0784314 | |
| I0331 11:13:13.898375 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.732955 | |
| I0331 11:13:13.898387 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.137255 | |
| I0331 11:13:13.898401 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.44257 (* 0.3 = 1.03277 loss) | |
| I0331 11:13:13.898416 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.07349 (* 0.3 = 0.322046 loss) | |
| I0331 11:13:13.898427 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.0392157 | |
| I0331 11:13:13.898438 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.721591 | |
| I0331 11:13:13.898450 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.156863 | |
| I0331 11:13:13.898464 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.26095 (* 1 = 3.26095 loss) | |
| I0331 11:13:13.898478 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 1.01067 (* 1 = 1.01067 loss) | |
| I0331 11:13:13.898489 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:13:13.898501 29371 solver.cpp:245] Train net output #16: total_confidence = 1.48358e-05 | |
| I0331 11:13:13.898514 29371 sgd_solver.cpp:106] Iteration 14000, lr = 0.005 | |
| I0331 11:15:22.951712 29371 solver.cpp:229] Iteration 14500, loss = 6.60763 | |
| I0331 11:15:22.951830 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.116279 | |
| I0331 11:15:22.951850 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.755682 | |
| I0331 11:15:22.951864 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.27907 | |
| I0331 11:15:22.951879 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.34055 (* 0.3 = 1.00217 loss) | |
| I0331 11:15:22.951894 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.02655 (* 0.3 = 0.307965 loss) | |
| I0331 11:15:22.951905 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0930233 | |
| I0331 11:15:22.951918 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.772727 | |
| I0331 11:15:22.951930 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.232558 | |
| I0331 11:15:22.951943 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.26111 (* 0.3 = 0.978332 loss) | |
| I0331 11:15:22.951957 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.959646 (* 0.3 = 0.287894 loss) | |
| I0331 11:15:22.951969 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.162791 | |
| I0331 11:15:22.951982 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.778409 | |
| I0331 11:15:22.951993 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.209302 | |
| I0331 11:15:22.952008 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.22468 (* 1 = 3.22468 loss) | |
| I0331 11:15:22.952021 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.940293 (* 1 = 0.940293 loss) | |
| I0331 11:15:22.952033 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:15:22.952044 29371 solver.cpp:245] Train net output #16: total_confidence = 2.88512e-06 | |
| I0331 11:15:22.952056 29371 sgd_solver.cpp:106] Iteration 14500, lr = 0.005 | |
| I0331 11:17:31.730821 29371 solver.cpp:338] Iteration 15000, Testing net (#0) | |
| I0331 11:18:01.572352 29371 solver.cpp:393] Test loss: 5.88051 | |
| I0331 11:18:01.572398 29371 solver.cpp:406] Test net output #0: loss1/accuracy = 0.138376 | |
| I0331 11:18:01.572414 29371 solver.cpp:406] Test net output #1: loss1/accuracy_incl_empty = 0.7875 | |
| I0331 11:18:01.572427 29371 solver.cpp:406] Test net output #2: loss1/accuracy_top3 = 0.34844 | |
| I0331 11:18:01.572443 29371 solver.cpp:406] Test net output #3: loss1/cross_entropy_loss = 3.35363 (* 0.3 = 1.00609 loss) | |
| I0331 11:18:01.572458 29371 solver.cpp:406] Test net output #4: loss1/cross_entropy_loss_incl_empty = 0.84464 (* 0.3 = 0.253392 loss) | |
| I0331 11:18:01.572470 29371 solver.cpp:406] Test net output #5: loss2/accuracy = 0.135904 | |
| I0331 11:18:01.572482 29371 solver.cpp:406] Test net output #6: loss2/accuracy_incl_empty = 0.786773 | |
| I0331 11:18:01.572494 29371 solver.cpp:406] Test net output #7: loss2/accuracy_top3 = 0.342 | |
| I0331 11:18:01.572509 29371 solver.cpp:406] Test net output #8: loss2/cross_entropy_loss = 3.02528 (* 0.3 = 0.907583 loss) | |
| I0331 11:18:01.572522 29371 solver.cpp:406] Test net output #9: loss2/cross_entropy_loss_incl_empty = 0.761654 (* 0.3 = 0.228496 loss) | |
| I0331 11:18:01.572535 29371 solver.cpp:406] Test net output #10: loss3/accuracy = 0.14738 | |
| I0331 11:18:01.572546 29371 solver.cpp:406] Test net output #11: loss3/accuracy_incl_empty = 0.784136 | |
| I0331 11:18:01.572557 29371 solver.cpp:406] Test net output #12: loss3/accuracy_top3 = 0.357339 | |
| I0331 11:18:01.572572 29371 solver.cpp:406] Test net output #13: loss3/cross_entropy_loss = 2.74995 (* 1 = 2.74995 loss) | |
| I0331 11:18:01.572585 29371 solver.cpp:406] Test net output #14: loss3/cross_entropy_loss_incl_empty = 0.734985 (* 1 = 0.734985 loss) | |
| I0331 11:18:01.572597 29371 solver.cpp:406] Test net output #15: total_accuracy = 0 | |
| I0331 11:18:01.572608 29371 solver.cpp:406] Test net output #16: total_confidence = 7.62009e-05 | |
| I0331 11:18:01.724376 29371 solver.cpp:229] Iteration 15000, loss = 6.57596 | |
| I0331 11:18:01.724427 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0192308 | |
| I0331 11:18:01.724444 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.710227 | |
| I0331 11:18:01.724457 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.192308 | |
| I0331 11:18:01.724472 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.73629 (* 0.3 = 1.12089 loss) | |
| I0331 11:18:01.724489 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.14076 (* 0.3 = 0.342228 loss) | |
| I0331 11:18:01.724501 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0384615 | |
| I0331 11:18:01.724514 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.710227 | |
| I0331 11:18:01.724526 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.153846 | |
| I0331 11:18:01.724539 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.53299 (* 0.3 = 1.0599 loss) | |
| I0331 11:18:01.724553 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.09205 (* 0.3 = 0.327614 loss) | |
| I0331 11:18:01.724565 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.0961538 | |
| I0331 11:18:01.724577 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.727273 | |
| I0331 11:18:01.724588 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.211538 | |
| I0331 11:18:01.724602 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.26367 (* 1 = 3.26367 loss) | |
| I0331 11:18:01.724616 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 1.01677 (* 1 = 1.01677 loss) | |
| I0331 11:18:01.724627 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:18:01.724639 29371 solver.cpp:245] Train net output #16: total_confidence = 5.59422e-07 | |
| I0331 11:18:01.724655 29371 sgd_solver.cpp:106] Iteration 15000, lr = 0.005 | |
| I0331 11:20:10.748051 29371 solver.cpp:229] Iteration 15500, loss = 6.58627 | |
| I0331 11:20:10.748425 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.1 | |
| I0331 11:20:10.748456 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.755682 | |
| I0331 11:20:10.748478 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.3 | |
| I0331 11:20:10.748505 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.13237 (* 0.3 = 0.93971 loss) | |
| I0331 11:20:10.748529 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.929001 (* 0.3 = 0.2787 loss) | |
| I0331 11:20:10.748551 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.15 | |
| I0331 11:20:10.748571 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.789773 | |
| I0331 11:20:10.748592 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.275 | |
| I0331 11:20:10.748615 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.06583 (* 0.3 = 0.919748 loss) | |
| I0331 11:20:10.748641 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.840736 (* 0.3 = 0.252221 loss) | |
| I0331 11:20:10.748663 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.1 | |
| I0331 11:20:10.748684 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.778409 | |
| I0331 11:20:10.748704 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.375 | |
| I0331 11:20:10.748728 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.88582 (* 1 = 2.88582 loss) | |
| I0331 11:20:10.748752 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.780122 (* 1 = 0.780122 loss) | |
| I0331 11:20:10.748774 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:20:10.748795 29371 solver.cpp:245] Train net output #16: total_confidence = 9.16993e-05 | |
| I0331 11:20:10.748814 29371 sgd_solver.cpp:106] Iteration 15500, lr = 0.005 | |
| I0331 11:22:20.037324 29371 solver.cpp:229] Iteration 16000, loss = 6.52745 | |
| I0331 11:22:20.037437 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0652174 | |
| I0331 11:22:20.037457 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.755682 | |
| I0331 11:22:20.037470 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.152174 | |
| I0331 11:22:20.037487 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.23584 (* 0.3 = 0.970752 loss) | |
| I0331 11:22:20.037502 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.903882 (* 0.3 = 0.271165 loss) | |
| I0331 11:22:20.037513 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0869565 | |
| I0331 11:22:20.037525 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.755682 | |
| I0331 11:22:20.037538 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.173913 | |
| I0331 11:22:20.037551 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.3759 (* 0.3 = 1.01277 loss) | |
| I0331 11:22:20.037564 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.936139 (* 0.3 = 0.280842 loss) | |
| I0331 11:22:20.037576 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.0652174 | |
| I0331 11:22:20.037588 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.75 | |
| I0331 11:22:20.037600 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.195652 | |
| I0331 11:22:20.037614 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.29372 (* 1 = 3.29372 loss) | |
| I0331 11:22:20.037627 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.911802 (* 1 = 0.911802 loss) | |
| I0331 11:22:20.037639 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:22:20.037657 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000374582 | |
| I0331 11:22:20.037669 29371 sgd_solver.cpp:106] Iteration 16000, lr = 0.005 | |
| I0331 11:24:29.104840 29371 solver.cpp:229] Iteration 16500, loss = 6.52296 | |
| I0331 11:24:29.104979 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.142857 | |
| I0331 11:24:29.104998 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.761364 | |
| I0331 11:24:29.105020 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.285714 | |
| I0331 11:24:29.105038 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.36063 (* 0.3 = 1.00819 loss) | |
| I0331 11:24:29.105064 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.989709 (* 0.3 = 0.296913 loss) | |
| I0331 11:24:29.105079 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.183673 | |
| I0331 11:24:29.105095 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.772727 | |
| I0331 11:24:29.105108 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.326531 | |
| I0331 11:24:29.105121 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.34549 (* 0.3 = 1.00365 loss) | |
| I0331 11:24:29.105135 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.969666 (* 0.3 = 0.2909 loss) | |
| I0331 11:24:29.105147 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.183673 | |
| I0331 11:24:29.105160 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.761364 | |
| I0331 11:24:29.105172 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.387755 | |
| I0331 11:24:29.105185 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.19224 (* 1 = 3.19224 loss) | |
| I0331 11:24:29.105200 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.962334 (* 1 = 0.962334 loss) | |
| I0331 11:24:29.105211 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:24:29.105222 29371 solver.cpp:245] Train net output #16: total_confidence = 2.02467e-05 | |
| I0331 11:24:29.105235 29371 sgd_solver.cpp:106] Iteration 16500, lr = 0.005 | |
| I0331 11:26:38.468819 29371 solver.cpp:229] Iteration 17000, loss = 6.52171 | |
| I0331 11:26:38.468937 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0638298 | |
| I0331 11:26:38.468957 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.738636 | |
| I0331 11:26:38.468977 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.297872 | |
| I0331 11:26:38.468992 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.86743 (* 0.3 = 1.16023 loss) | |
| I0331 11:26:38.469007 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.14609 (* 0.3 = 0.343826 loss) | |
| I0331 11:26:38.469019 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0638298 | |
| I0331 11:26:38.469032 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.738636 | |
| I0331 11:26:38.469043 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.212766 | |
| I0331 11:26:38.469056 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 4.04833 (* 0.3 = 1.2145 loss) | |
| I0331 11:26:38.469070 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.1875 (* 0.3 = 0.35625 loss) | |
| I0331 11:26:38.469085 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.0851064 | |
| I0331 11:26:38.469099 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.744318 | |
| I0331 11:26:38.469110 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.234043 | |
| I0331 11:26:38.469123 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.78926 (* 1 = 3.78926 loss) | |
| I0331 11:26:38.469137 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 1.12393 (* 1 = 1.12393 loss) | |
| I0331 11:26:38.469149 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:26:38.469161 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000198103 | |
| I0331 11:26:38.469173 29371 sgd_solver.cpp:106] Iteration 17000, lr = 0.005 | |
| I0331 11:28:47.638075 29371 solver.cpp:229] Iteration 17500, loss = 6.42424 | |
| I0331 11:28:47.638207 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.05 | |
| I0331 11:28:47.638227 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.738636 | |
| I0331 11:28:47.638241 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.225 | |
| I0331 11:28:47.638264 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 4.01245 (* 0.3 = 1.20374 loss) | |
| I0331 11:28:47.638284 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.24099 (* 0.3 = 0.372297 loss) | |
| I0331 11:28:47.638303 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.05 | |
| I0331 11:28:47.638316 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.75 | |
| I0331 11:28:47.638329 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.225 | |
| I0331 11:28:47.638342 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.86421 (* 0.3 = 1.15926 loss) | |
| I0331 11:28:47.638356 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.17127 (* 0.3 = 0.35138 loss) | |
| I0331 11:28:47.638368 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.075 | |
| I0331 11:28:47.638381 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.75 | |
| I0331 11:28:47.638392 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.25 | |
| I0331 11:28:47.638406 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.7467 (* 1 = 3.7467 loss) | |
| I0331 11:28:47.638419 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 1.05844 (* 1 = 1.05844 loss) | |
| I0331 11:28:47.638432 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:28:47.638442 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000331391 | |
| I0331 11:28:47.638454 29371 sgd_solver.cpp:106] Iteration 17500, lr = 0.005 | |
| I0331 11:30:56.714853 29371 solver.cpp:229] Iteration 18000, loss = 6.44845 | |
| I0331 11:30:56.714990 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.111111 | |
| I0331 11:30:56.715010 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.761364 | |
| I0331 11:30:56.715023 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.244444 | |
| I0331 11:30:56.715039 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.14151 (* 0.3 = 0.942453 loss) | |
| I0331 11:30:56.715054 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.904879 (* 0.3 = 0.271464 loss) | |
| I0331 11:30:56.715066 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.133333 | |
| I0331 11:30:56.715078 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.767045 | |
| I0331 11:30:56.715108 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.288889 | |
| I0331 11:30:56.715123 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.14408 (* 0.3 = 0.943225 loss) | |
| I0331 11:30:56.715137 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.940586 (* 0.3 = 0.282176 loss) | |
| I0331 11:30:56.715149 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.111111 | |
| I0331 11:30:56.715162 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.767045 | |
| I0331 11:30:56.715173 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.311111 | |
| I0331 11:30:56.715188 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.01983 (* 1 = 3.01983 loss) | |
| I0331 11:30:56.715200 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.86118 (* 1 = 0.86118 loss) | |
| I0331 11:30:56.715212 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:30:56.715224 29371 solver.cpp:245] Train net output #16: total_confidence = 7.28542e-06 | |
| I0331 11:30:56.715237 29371 sgd_solver.cpp:106] Iteration 18000, lr = 0.005 | |
| I0331 11:33:05.658865 29371 solver.cpp:229] Iteration 18500, loss = 6.41203 | |
| I0331 11:33:05.659234 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0625 | |
| I0331 11:33:05.659263 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.744318 | |
| I0331 11:33:05.659286 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.208333 | |
| I0331 11:33:05.659313 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.38254 (* 0.3 = 1.01476 loss) | |
| I0331 11:33:05.659338 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.960928 (* 0.3 = 0.288278 loss) | |
| I0331 11:33:05.659360 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.104167 | |
| I0331 11:33:05.659382 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.755682 | |
| I0331 11:33:05.659402 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.208333 | |
| I0331 11:33:05.659427 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.35059 (* 0.3 = 1.00518 loss) | |
| I0331 11:33:05.659452 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.00659 (* 0.3 = 0.301977 loss) | |
| I0331 11:33:05.659472 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.0833333 | |
| I0331 11:33:05.659494 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.75 | |
| I0331 11:33:05.659515 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.270833 | |
| I0331 11:33:05.659539 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.23724 (* 1 = 3.23724 loss) | |
| I0331 11:33:05.659564 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.931142 (* 1 = 0.931142 loss) | |
| I0331 11:33:05.659585 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:33:05.659605 29371 solver.cpp:245] Train net output #16: total_confidence = 3.03388e-05 | |
| I0331 11:33:05.659626 29371 sgd_solver.cpp:106] Iteration 18500, lr = 0.005 | |
| I0331 11:35:14.691890 29371 solver.cpp:229] Iteration 19000, loss = 6.4003 | |
| I0331 11:35:14.692021 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.142857 | |
| I0331 11:35:14.692041 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.772727 | |
| I0331 11:35:14.692054 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.261905 | |
| I0331 11:35:14.692070 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.5825 (* 0.3 = 1.07475 loss) | |
| I0331 11:35:14.692087 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.03737 (* 0.3 = 0.31121 loss) | |
| I0331 11:35:14.692101 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0952381 | |
| I0331 11:35:14.692113 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.767045 | |
| I0331 11:35:14.692126 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.261905 | |
| I0331 11:35:14.692139 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.42495 (* 0.3 = 1.02749 loss) | |
| I0331 11:35:14.692152 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.957461 (* 0.3 = 0.287238 loss) | |
| I0331 11:35:14.692164 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.119048 | |
| I0331 11:35:14.692176 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.772727 | |
| I0331 11:35:14.692188 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.285714 | |
| I0331 11:35:14.692201 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.47238 (* 1 = 3.47238 loss) | |
| I0331 11:35:14.692215 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.953992 (* 1 = 0.953992 loss) | |
| I0331 11:35:14.692229 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:35:14.692239 29371 solver.cpp:245] Train net output #16: total_confidence = 5.01732e-05 | |
| I0331 11:35:14.692252 29371 sgd_solver.cpp:106] Iteration 19000, lr = 0.005 | |
| I0331 11:37:23.771651 29371 solver.cpp:229] Iteration 19500, loss = 6.42031 | |
| I0331 11:37:23.771790 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0952381 | |
| I0331 11:37:23.771811 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.761364 | |
| I0331 11:37:23.771833 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.285714 | |
| I0331 11:37:23.771849 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.32304 (* 0.3 = 0.996911 loss) | |
| I0331 11:37:23.771863 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.952886 (* 0.3 = 0.285866 loss) | |
| I0331 11:37:23.771877 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0714286 | |
| I0331 11:37:23.771888 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.761364 | |
| I0331 11:37:23.771900 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.309524 | |
| I0331 11:37:23.771914 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.19792 (* 0.3 = 0.959377 loss) | |
| I0331 11:37:23.771929 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.930767 (* 0.3 = 0.27923 loss) | |
| I0331 11:37:23.771950 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.142857 | |
| I0331 11:37:23.771961 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.778409 | |
| I0331 11:37:23.771973 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.309524 | |
| I0331 11:37:23.771991 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.13913 (* 1 = 3.13913 loss) | |
| I0331 11:37:23.772023 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.872003 (* 1 = 0.872003 loss) | |
| I0331 11:37:23.772056 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:37:23.772078 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000402748 | |
| I0331 11:37:23.772105 29371 sgd_solver.cpp:106] Iteration 19500, lr = 0.005 | |
| I0331 11:39:32.614279 29371 solver.cpp:338] Iteration 20000, Testing net (#0) | |
| I0331 11:40:02.364620 29371 solver.cpp:393] Test loss: 6.81304 | |
| I0331 11:40:02.364670 29371 solver.cpp:406] Test net output #0: loss1/accuracy = 0.119562 | |
| I0331 11:40:02.364688 29371 solver.cpp:406] Test net output #1: loss1/accuracy_incl_empty = 0.782773 | |
| I0331 11:40:02.364701 29371 solver.cpp:406] Test net output #2: loss1/accuracy_top3 = 0.304496 | |
| I0331 11:40:02.364717 29371 solver.cpp:406] Test net output #3: loss1/cross_entropy_loss = 3.40198 (* 0.3 = 1.02059 loss) | |
| I0331 11:40:02.364732 29371 solver.cpp:406] Test net output #4: loss1/cross_entropy_loss_incl_empty = 0.859039 (* 0.3 = 0.257712 loss) | |
| I0331 11:40:02.364743 29371 solver.cpp:406] Test net output #5: loss2/accuracy = 0.090269 | |
| I0331 11:40:02.364756 29371 solver.cpp:406] Test net output #6: loss2/accuracy_incl_empty = 0.775046 | |
| I0331 11:40:02.364768 29371 solver.cpp:406] Test net output #7: loss2/accuracy_top3 = 0.248366 | |
| I0331 11:40:02.364781 29371 solver.cpp:406] Test net output #8: loss2/cross_entropy_loss = 3.45116 (* 0.3 = 1.03535 loss) | |
| I0331 11:40:02.364794 29371 solver.cpp:406] Test net output #9: loss2/cross_entropy_loss_incl_empty = 0.890512 (* 0.3 = 0.267154 loss) | |
| I0331 11:40:02.364806 29371 solver.cpp:406] Test net output #10: loss3/accuracy = 0.0969321 | |
| I0331 11:40:02.364819 29371 solver.cpp:406] Test net output #11: loss3/accuracy_incl_empty = 0.771954 | |
| I0331 11:40:02.364830 29371 solver.cpp:406] Test net output #12: loss3/accuracy_top3 = 0.276718 | |
| I0331 11:40:02.364843 29371 solver.cpp:406] Test net output #13: loss3/cross_entropy_loss = 3.33988 (* 1 = 3.33988 loss) | |
| I0331 11:40:02.364856 29371 solver.cpp:406] Test net output #14: loss3/cross_entropy_loss_incl_empty = 0.892348 (* 1 = 0.892348 loss) | |
| I0331 11:40:02.364868 29371 solver.cpp:406] Test net output #15: total_accuracy = 0 | |
| I0331 11:40:02.364879 29371 solver.cpp:406] Test net output #16: total_confidence = 0.000166657 | |
| I0331 11:40:02.515489 29371 solver.cpp:229] Iteration 20000, loss = 6.33894 | |
| I0331 11:40:02.515528 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0697674 | |
| I0331 11:40:02.515544 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.755682 | |
| I0331 11:40:02.515558 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.186047 | |
| I0331 11:40:02.515573 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.42843 (* 0.3 = 1.02853 loss) | |
| I0331 11:40:02.515586 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.968865 (* 0.3 = 0.29066 loss) | |
| I0331 11:40:02.515599 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0232558 | |
| I0331 11:40:02.515610 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.744318 | |
| I0331 11:40:02.515622 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.232558 | |
| I0331 11:40:02.515636 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.3915 (* 0.3 = 1.01745 loss) | |
| I0331 11:40:02.515653 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.936576 (* 0.3 = 0.280973 loss) | |
| I0331 11:40:02.515666 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.0930233 | |
| I0331 11:40:02.515678 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.767045 | |
| I0331 11:40:02.515689 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.27907 | |
| I0331 11:40:02.515703 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.22926 (* 1 = 3.22926 loss) | |
| I0331 11:40:02.515717 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.903762 (* 1 = 0.903762 loss) | |
| I0331 11:40:02.515728 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:40:02.515740 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000964639 | |
| I0331 11:40:02.515753 29371 sgd_solver.cpp:106] Iteration 20000, lr = 0.005 | |
| I0331 11:42:11.423058 29371 solver.cpp:229] Iteration 20500, loss = 6.36647 | |
| I0331 11:42:11.423202 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0833333 | |
| I0331 11:42:11.423223 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.75 | |
| I0331 11:42:11.423244 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.208333 | |
| I0331 11:42:11.423260 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.13144 (* 0.3 = 0.939431 loss) | |
| I0331 11:42:11.423274 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.904795 (* 0.3 = 0.271438 loss) | |
| I0331 11:42:11.423287 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0416667 | |
| I0331 11:42:11.423300 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.732955 | |
| I0331 11:42:11.423311 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.229167 | |
| I0331 11:42:11.423324 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.11136 (* 0.3 = 0.933407 loss) | |
| I0331 11:42:11.423338 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.897604 (* 0.3 = 0.269281 loss) | |
| I0331 11:42:11.423351 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.0416667 | |
| I0331 11:42:11.423362 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.738636 | |
| I0331 11:42:11.423374 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.25 | |
| I0331 11:42:11.423388 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.92357 (* 1 = 2.92357 loss) | |
| I0331 11:42:11.423401 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.829513 (* 1 = 0.829513 loss) | |
| I0331 11:42:11.423413 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:42:11.423424 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000118272 | |
| I0331 11:42:11.423437 29371 sgd_solver.cpp:106] Iteration 20500, lr = 0.005 | |
| I0331 11:44:20.437943 29371 solver.cpp:229] Iteration 21000, loss = 6.32762 | |
| I0331 11:44:20.438102 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.162162 | |
| I0331 11:44:20.438140 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.778409 | |
| I0331 11:44:20.438164 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.27027 | |
| I0331 11:44:20.438191 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.03612 (* 0.3 = 0.910836 loss) | |
| I0331 11:44:20.438217 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.919047 (* 0.3 = 0.275714 loss) | |
| I0331 11:44:20.438240 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.135135 | |
| I0331 11:44:20.438263 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.789773 | |
| I0331 11:44:20.438285 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.324324 | |
| I0331 11:44:20.438311 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.96892 (* 0.3 = 0.890675 loss) | |
| I0331 11:44:20.438338 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.849045 (* 0.3 = 0.254714 loss) | |
| I0331 11:44:20.438359 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.135135 | |
| I0331 11:44:20.438380 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.784091 | |
| I0331 11:44:20.438402 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.351351 | |
| I0331 11:44:20.438427 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.831 (* 1 = 2.831 loss) | |
| I0331 11:44:20.438452 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.82658 (* 1 = 0.82658 loss) | |
| I0331 11:44:20.438472 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:44:20.438494 29371 solver.cpp:245] Train net output #16: total_confidence = 0.00120338 | |
| I0331 11:44:20.438515 29371 sgd_solver.cpp:106] Iteration 21000, lr = 0.005 | |
| I0331 11:46:29.664868 29371 solver.cpp:229] Iteration 21500, loss = 6.3404 | |
| I0331 11:46:29.664988 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.113636 | |
| I0331 11:46:29.665009 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.761364 | |
| I0331 11:46:29.665022 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.25 | |
| I0331 11:46:29.665040 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.8948 (* 0.3 = 0.868441 loss) | |
| I0331 11:46:29.665053 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.817344 (* 0.3 = 0.245203 loss) | |
| I0331 11:46:29.665066 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.204545 | |
| I0331 11:46:29.665078 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.789773 | |
| I0331 11:46:29.665093 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.227273 | |
| I0331 11:46:29.665107 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.78721 (* 0.3 = 0.836164 loss) | |
| I0331 11:46:29.665122 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.784034 (* 0.3 = 0.23521 loss) | |
| I0331 11:46:29.665133 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.0909091 | |
| I0331 11:46:29.665145 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.767045 | |
| I0331 11:46:29.665156 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.25 | |
| I0331 11:46:29.665169 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.67742 (* 1 = 2.67742 loss) | |
| I0331 11:46:29.665184 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.721794 (* 1 = 0.721794 loss) | |
| I0331 11:46:29.665195 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:46:29.665207 29371 solver.cpp:245] Train net output #16: total_confidence = 8.99648e-05 | |
| I0331 11:46:29.665220 29371 sgd_solver.cpp:106] Iteration 21500, lr = 0.005 | |
| I0331 11:48:38.752599 29371 solver.cpp:229] Iteration 22000, loss = 6.30076 | |
| I0331 11:48:38.752724 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.117647 | |
| I0331 11:48:38.752745 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.738636 | |
| I0331 11:48:38.752758 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.215686 | |
| I0331 11:48:38.752774 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.05886 (* 0.3 = 0.917659 loss) | |
| I0331 11:48:38.752789 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.978632 (* 0.3 = 0.29359 loss) | |
| I0331 11:48:38.752800 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.137255 | |
| I0331 11:48:38.752813 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.744318 | |
| I0331 11:48:38.752825 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.313726 | |
| I0331 11:48:38.752838 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.01704 (* 0.3 = 0.905111 loss) | |
| I0331 11:48:38.752852 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.9339 (* 0.3 = 0.28017 loss) | |
| I0331 11:48:38.752864 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.176471 | |
| I0331 11:48:38.752876 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.761364 | |
| I0331 11:48:38.752888 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.392157 | |
| I0331 11:48:38.752902 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.77976 (* 1 = 2.77976 loss) | |
| I0331 11:48:38.752917 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.857426 (* 1 = 0.857426 loss) | |
| I0331 11:48:38.752928 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:48:38.752939 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000172198 | |
| I0331 11:48:38.752951 29371 sgd_solver.cpp:106] Iteration 22000, lr = 0.005 | |
| I0331 11:50:47.816555 29371 solver.cpp:229] Iteration 22500, loss = 6.24734 | |
| I0331 11:50:47.816675 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.186047 | |
| I0331 11:50:47.816705 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.772727 | |
| I0331 11:50:47.816730 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.395349 | |
| I0331 11:50:47.816757 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.80236 (* 0.3 = 0.840707 loss) | |
| I0331 11:50:47.816784 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.839492 (* 0.3 = 0.251848 loss) | |
| I0331 11:50:47.816810 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.186047 | |
| I0331 11:50:47.816833 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.784091 | |
| I0331 11:50:47.816854 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.395349 | |
| I0331 11:50:47.816879 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.76827 (* 0.3 = 0.83048 loss) | |
| I0331 11:50:47.816905 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.779879 (* 0.3 = 0.233964 loss) | |
| I0331 11:50:47.816927 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.162791 | |
| I0331 11:50:47.816948 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.784091 | |
| I0331 11:50:47.816969 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.488372 | |
| I0331 11:50:47.816993 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.64152 (* 1 = 2.64152 loss) | |
| I0331 11:50:47.817018 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.742239 (* 1 = 0.742239 loss) | |
| I0331 11:50:47.817040 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:50:47.817060 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000215241 | |
| I0331 11:50:47.817085 29371 sgd_solver.cpp:106] Iteration 22500, lr = 0.005 | |
| I0331 11:52:56.803467 29371 solver.cpp:229] Iteration 23000, loss = 6.17095 | |
| I0331 11:52:56.803616 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0980392 | |
| I0331 11:52:56.803642 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.732955 | |
| I0331 11:52:56.803660 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.333333 | |
| I0331 11:52:56.803684 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.07964 (* 0.3 = 0.923892 loss) | |
| I0331 11:52:56.803705 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.986803 (* 0.3 = 0.296041 loss) | |
| I0331 11:52:56.803722 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.176471 | |
| I0331 11:52:56.803740 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.738636 | |
| I0331 11:52:56.803757 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.352941 | |
| I0331 11:52:56.803776 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.05142 (* 0.3 = 0.915427 loss) | |
| I0331 11:52:56.803797 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.0433 (* 0.3 = 0.312991 loss) | |
| I0331 11:52:56.803815 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.137255 | |
| I0331 11:52:56.803836 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.738636 | |
| I0331 11:52:56.803858 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.392157 | |
| I0331 11:52:56.803884 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.95245 (* 1 = 2.95245 loss) | |
| I0331 11:52:56.803912 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.937721 (* 1 = 0.937721 loss) | |
| I0331 11:52:56.803932 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:52:56.803954 29371 solver.cpp:245] Train net output #16: total_confidence = 5.24693e-06 | |
| I0331 11:52:56.803987 29371 sgd_solver.cpp:106] Iteration 23000, lr = 0.005 | |
| I0331 11:55:05.648454 29371 solver.cpp:229] Iteration 23500, loss = 6.21126 | |
| I0331 11:55:05.648608 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0833333 | |
| I0331 11:55:05.648629 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.75 | |
| I0331 11:55:05.648643 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.3125 | |
| I0331 11:55:05.648659 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.02583 (* 0.3 = 0.907749 loss) | |
| I0331 11:55:05.648674 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.878588 (* 0.3 = 0.263576 loss) | |
| I0331 11:55:05.648686 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.166667 | |
| I0331 11:55:05.648699 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.772727 | |
| I0331 11:55:05.648710 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.333333 | |
| I0331 11:55:05.648725 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.89876 (* 0.3 = 0.869628 loss) | |
| I0331 11:55:05.648737 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.837305 (* 0.3 = 0.251192 loss) | |
| I0331 11:55:05.648751 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.125 | |
| I0331 11:55:05.648762 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.755682 | |
| I0331 11:55:05.648774 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.354167 | |
| I0331 11:55:05.648788 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.71961 (* 1 = 2.71961 loss) | |
| I0331 11:55:05.648802 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.791434 (* 1 = 0.791434 loss) | |
| I0331 11:55:05.648814 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:55:05.648825 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000107772 | |
| I0331 11:55:05.648838 29371 sgd_solver.cpp:106] Iteration 23500, lr = 0.005 | |
| I0331 11:57:14.934633 29371 solver.cpp:229] Iteration 24000, loss = 6.19615 | |
| I0331 11:57:14.934806 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0487805 | |
| I0331 11:57:14.934846 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.772727 | |
| I0331 11:57:14.934872 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.292683 | |
| I0331 11:57:14.934895 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.11811 (* 0.3 = 0.935433 loss) | |
| I0331 11:57:14.934911 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.813413 (* 0.3 = 0.244024 loss) | |
| I0331 11:57:14.934923 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.121951 | |
| I0331 11:57:14.934937 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.784091 | |
| I0331 11:57:14.934949 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.365854 | |
| I0331 11:57:14.934963 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.88862 (* 0.3 = 0.866587 loss) | |
| I0331 11:57:14.934976 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.753864 (* 0.3 = 0.226159 loss) | |
| I0331 11:57:14.934988 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.146341 | |
| I0331 11:57:14.935000 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.784091 | |
| I0331 11:57:14.935012 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.317073 | |
| I0331 11:57:14.935026 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.78008 (* 1 = 2.78008 loss) | |
| I0331 11:57:14.935039 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.753644 (* 1 = 0.753644 loss) | |
| I0331 11:57:14.935051 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:57:14.935063 29371 solver.cpp:245] Train net output #16: total_confidence = 9.91696e-05 | |
| I0331 11:57:14.935076 29371 sgd_solver.cpp:106] Iteration 24000, lr = 0.005 | |
| I0331 11:59:24.043004 29371 solver.cpp:229] Iteration 24500, loss = 6.18117 | |
| I0331 11:59:24.043082 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.133333 | |
| I0331 11:59:24.043103 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.75 | |
| I0331 11:59:24.043117 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.266667 | |
| I0331 11:59:24.043148 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.32774 (* 0.3 = 0.998321 loss) | |
| I0331 11:59:24.043165 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.998225 (* 0.3 = 0.299468 loss) | |
| I0331 11:59:24.043177 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.222222 | |
| I0331 11:59:24.043190 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.772727 | |
| I0331 11:59:24.043200 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.377778 | |
| I0331 11:59:24.043215 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.22758 (* 0.3 = 0.968273 loss) | |
| I0331 11:59:24.043227 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.967581 (* 0.3 = 0.290274 loss) | |
| I0331 11:59:24.043239 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.266667 | |
| I0331 11:59:24.043251 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.778409 | |
| I0331 11:59:24.043263 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.444444 | |
| I0331 11:59:24.043277 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.97293 (* 1 = 2.97293 loss) | |
| I0331 11:59:24.043290 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.896119 (* 1 = 0.896119 loss) | |
| I0331 11:59:24.043303 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 11:59:24.043313 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000667035 | |
| I0331 11:59:24.043326 29371 sgd_solver.cpp:106] Iteration 24500, lr = 0.005 | |
| I0331 12:01:33.549535 29371 solver.cpp:338] Iteration 25000, Testing net (#0) | |
| I0331 12:02:03.387682 29371 solver.cpp:393] Test loss: 5.98537 | |
| I0331 12:02:03.387732 29371 solver.cpp:406] Test net output #0: loss1/accuracy = 0.136854 | |
| I0331 12:02:03.387748 29371 solver.cpp:406] Test net output #1: loss1/accuracy_incl_empty = 0.786455 | |
| I0331 12:02:03.387760 29371 solver.cpp:406] Test net output #2: loss1/accuracy_top3 = 0.354266 | |
| I0331 12:02:03.387776 29371 solver.cpp:406] Test net output #3: loss1/cross_entropy_loss = 2.97385 (* 0.3 = 0.892156 loss) | |
| I0331 12:02:03.387790 29371 solver.cpp:406] Test net output #4: loss1/cross_entropy_loss_incl_empty = 0.758902 (* 0.3 = 0.227671 loss) | |
| I0331 12:02:03.387802 29371 solver.cpp:406] Test net output #5: loss2/accuracy = 0.134996 | |
| I0331 12:02:03.387814 29371 solver.cpp:406] Test net output #6: loss2/accuracy_incl_empty = 0.786 | |
| I0331 12:02:03.387825 29371 solver.cpp:406] Test net output #7: loss2/accuracy_top3 = 0.331848 | |
| I0331 12:02:03.387840 29371 solver.cpp:406] Test net output #8: loss2/cross_entropy_loss = 2.99386 (* 0.3 = 0.898159 loss) | |
| I0331 12:02:03.387853 29371 solver.cpp:406] Test net output #9: loss2/cross_entropy_loss_incl_empty = 0.765033 (* 0.3 = 0.22951 loss) | |
| I0331 12:02:03.387866 29371 solver.cpp:406] Test net output #10: loss3/accuracy = 0.144693 | |
| I0331 12:02:03.387877 29371 solver.cpp:406] Test net output #11: loss3/accuracy_incl_empty = 0.785773 | |
| I0331 12:02:03.387888 29371 solver.cpp:406] Test net output #12: loss3/accuracy_top3 = 0.384902 | |
| I0331 12:02:03.387902 29371 solver.cpp:406] Test net output #13: loss3/cross_entropy_loss = 2.96506 (* 1 = 2.96506 loss) | |
| I0331 12:02:03.387915 29371 solver.cpp:406] Test net output #14: loss3/cross_entropy_loss_incl_empty = 0.77281 (* 1 = 0.77281 loss) | |
| I0331 12:02:03.387926 29371 solver.cpp:406] Test net output #15: total_accuracy = 0 | |
| I0331 12:02:03.387938 29371 solver.cpp:406] Test net output #16: total_confidence = 0.00147571 | |
| I0331 12:02:03.539115 29371 solver.cpp:229] Iteration 25000, loss = 6.15388 | |
| I0331 12:02:03.539165 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0612245 | |
| I0331 12:02:03.539180 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.721591 | |
| I0331 12:02:03.539192 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.142857 | |
| I0331 12:02:03.539207 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.49006 (* 0.3 = 1.04702 loss) | |
| I0331 12:02:03.539222 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.11959 (* 0.3 = 0.335876 loss) | |
| I0331 12:02:03.539233 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.102041 | |
| I0331 12:02:03.539245 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.744318 | |
| I0331 12:02:03.539258 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.22449 | |
| I0331 12:02:03.539271 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.44179 (* 0.3 = 1.03254 loss) | |
| I0331 12:02:03.539285 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.0654 (* 0.3 = 0.319621 loss) | |
| I0331 12:02:03.539297 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.122449 | |
| I0331 12:02:03.539309 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.738636 | |
| I0331 12:02:03.539320 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.326531 | |
| I0331 12:02:03.539335 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 3.24491 (* 1 = 3.24491 loss) | |
| I0331 12:02:03.539347 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 1.01257 (* 1 = 1.01257 loss) | |
| I0331 12:02:03.539360 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:02:03.539371 29371 solver.cpp:245] Train net output #16: total_confidence = 5.27663e-05 | |
| I0331 12:02:03.539382 29371 sgd_solver.cpp:106] Iteration 25000, lr = 0.005 | |
| I0331 12:04:12.387660 29371 solver.cpp:229] Iteration 25500, loss = 6.16887 | |
| I0331 12:04:12.387804 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.102564 | |
| I0331 12:04:12.387835 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.784091 | |
| I0331 12:04:12.387858 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.230769 | |
| I0331 12:04:12.387886 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.19141 (* 0.3 = 0.957424 loss) | |
| I0331 12:04:12.387913 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.842914 (* 0.3 = 0.252874 loss) | |
| I0331 12:04:12.387938 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.102564 | |
| I0331 12:04:12.387961 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.784091 | |
| I0331 12:04:12.387982 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.25641 | |
| I0331 12:04:12.388006 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.03819 (* 0.3 = 0.911456 loss) | |
| I0331 12:04:12.388031 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.795598 (* 0.3 = 0.238679 loss) | |
| I0331 12:04:12.388053 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.205128 | |
| I0331 12:04:12.388073 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.806818 | |
| I0331 12:04:12.388099 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.435897 | |
| I0331 12:04:12.388124 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.78519 (* 1 = 2.78519 loss) | |
| I0331 12:04:12.388150 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.723668 (* 1 = 0.723668 loss) | |
| I0331 12:04:12.388171 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:04:12.388191 29371 solver.cpp:245] Train net output #16: total_confidence = 9.60823e-05 | |
| I0331 12:04:12.388213 29371 sgd_solver.cpp:106] Iteration 25500, lr = 0.005 | |
| I0331 12:06:21.407563 29371 solver.cpp:229] Iteration 26000, loss = 6.11499 | |
| I0331 12:06:21.407680 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0714286 | |
| I0331 12:06:21.407699 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.767045 | |
| I0331 12:06:21.407711 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.261905 | |
| I0331 12:06:21.407728 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.17363 (* 0.3 = 0.95209 loss) | |
| I0331 12:06:21.407743 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.871933 (* 0.3 = 0.26158 loss) | |
| I0331 12:06:21.407755 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0952381 | |
| I0331 12:06:21.407768 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.772727 | |
| I0331 12:06:21.407780 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.214286 | |
| I0331 12:06:21.407794 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.28118 (* 0.3 = 0.984355 loss) | |
| I0331 12:06:21.407809 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.884799 (* 0.3 = 0.26544 loss) | |
| I0331 12:06:21.407820 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.214286 | |
| I0331 12:06:21.407846 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.795455 | |
| I0331 12:06:21.407860 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.380952 | |
| I0331 12:06:21.407874 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.91866 (* 1 = 2.91866 loss) | |
| I0331 12:06:21.407888 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.784071 (* 1 = 0.784071 loss) | |
| I0331 12:06:21.407909 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:06:21.407920 29371 solver.cpp:245] Train net output #16: total_confidence = 0.00165875 | |
| I0331 12:06:21.407933 29371 sgd_solver.cpp:106] Iteration 26000, lr = 0.005 | |
| I0331 12:08:31.114663 29371 solver.cpp:229] Iteration 26500, loss = 6.06823 | |
| I0331 12:08:31.114814 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.06 | |
| I0331 12:08:31.114852 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.727273 | |
| I0331 12:08:31.114877 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.18 | |
| I0331 12:08:31.114907 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.17162 (* 0.3 = 0.951485 loss) | |
| I0331 12:08:31.114926 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.989832 (* 0.3 = 0.29695 loss) | |
| I0331 12:08:31.114939 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.12 | |
| I0331 12:08:31.114953 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.727273 | |
| I0331 12:08:31.114964 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.22 | |
| I0331 12:08:31.114977 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.18628 (* 0.3 = 0.955885 loss) | |
| I0331 12:08:31.114991 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.01571 (* 0.3 = 0.304713 loss) | |
| I0331 12:08:31.115003 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.2 | |
| I0331 12:08:31.115015 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.75 | |
| I0331 12:08:31.115027 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.38 | |
| I0331 12:08:31.115042 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.79165 (* 1 = 2.79165 loss) | |
| I0331 12:08:31.115077 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.902947 (* 1 = 0.902947 loss) | |
| I0331 12:08:31.115129 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:08:31.115152 29371 solver.cpp:245] Train net output #16: total_confidence = 9.44554e-05 | |
| I0331 12:08:31.115175 29371 sgd_solver.cpp:106] Iteration 26500, lr = 0.005 | |
| I0331 12:10:40.218683 29371 solver.cpp:229] Iteration 27000, loss = 6.05843 | |
| I0331 12:10:40.218801 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.152174 | |
| I0331 12:10:40.218830 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.772727 | |
| I0331 12:10:40.218854 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.304348 | |
| I0331 12:10:40.218881 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.77739 (* 0.3 = 0.833217 loss) | |
| I0331 12:10:40.218909 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.789514 (* 0.3 = 0.236854 loss) | |
| I0331 12:10:40.218931 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.130435 | |
| I0331 12:10:40.218955 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.772727 | |
| I0331 12:10:40.218977 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.282609 | |
| I0331 12:10:40.219003 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.79661 (* 0.3 = 0.838982 loss) | |
| I0331 12:10:40.219027 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.775566 (* 0.3 = 0.23267 loss) | |
| I0331 12:10:40.219048 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.152174 | |
| I0331 12:10:40.219069 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.772727 | |
| I0331 12:10:40.219089 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.391304 | |
| I0331 12:10:40.219135 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.55339 (* 1 = 2.55339 loss) | |
| I0331 12:10:40.219162 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.730481 (* 1 = 0.730481 loss) | |
| I0331 12:10:40.219184 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:10:40.219205 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000225542 | |
| I0331 12:10:40.219226 29371 sgd_solver.cpp:106] Iteration 27000, lr = 0.005 | |
| I0331 12:12:49.312083 29371 solver.cpp:229] Iteration 27500, loss = 6.01024 | |
| I0331 12:12:49.312245 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.142857 | |
| I0331 12:12:49.312265 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.767045 | |
| I0331 12:12:49.312288 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.333333 | |
| I0331 12:12:49.312302 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.86777 (* 0.3 = 1.16033 loss) | |
| I0331 12:12:49.312317 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.11632 (* 0.3 = 0.334896 loss) | |
| I0331 12:12:49.312330 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.142857 | |
| I0331 12:12:49.312342 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.761364 | |
| I0331 12:12:49.312353 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.309524 | |
| I0331 12:12:49.312368 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.54759 (* 0.3 = 1.06428 loss) | |
| I0331 12:12:49.312382 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.06773 (* 0.3 = 0.32032 loss) | |
| I0331 12:12:49.312394 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.214286 | |
| I0331 12:12:49.312407 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.772727 | |
| I0331 12:12:49.312418 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.357143 | |
| I0331 12:12:49.312432 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.79944 (* 1 = 2.79944 loss) | |
| I0331 12:12:49.312451 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.917792 (* 1 = 0.917792 loss) | |
| I0331 12:12:49.312482 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:12:49.312505 29371 solver.cpp:245] Train net output #16: total_confidence = 1.17351e-05 | |
| I0331 12:12:49.312536 29371 sgd_solver.cpp:106] Iteration 27500, lr = 0.005 | |
| I0331 12:14:58.382386 29371 solver.cpp:229] Iteration 28000, loss = 6.04725 | |
| I0331 12:14:58.382499 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.12 | |
| I0331 12:14:58.382520 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.75 | |
| I0331 12:14:58.382534 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.28 | |
| I0331 12:14:58.382550 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.94116 (* 0.3 = 0.882349 loss) | |
| I0331 12:14:58.382563 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.903129 (* 0.3 = 0.270939 loss) | |
| I0331 12:14:58.382575 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.22 | |
| I0331 12:14:58.382588 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.778409 | |
| I0331 12:14:58.382601 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.42 | |
| I0331 12:14:58.382614 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.92698 (* 0.3 = 0.878094 loss) | |
| I0331 12:14:58.382628 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.897841 (* 0.3 = 0.269352 loss) | |
| I0331 12:14:58.382640 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.2 | |
| I0331 12:14:58.382652 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.755682 | |
| I0331 12:14:58.382664 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.34 | |
| I0331 12:14:58.382679 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.65721 (* 1 = 2.65721 loss) | |
| I0331 12:14:58.382694 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.814149 (* 1 = 0.814149 loss) | |
| I0331 12:14:58.382714 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:14:58.382733 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000445462 | |
| I0331 12:14:58.382746 29371 sgd_solver.cpp:106] Iteration 28000, lr = 0.005 | |
| I0331 12:17:07.321985 29371 solver.cpp:229] Iteration 28500, loss = 5.96416 | |
| I0331 12:17:07.322130 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.163265 | |
| I0331 12:17:07.322150 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.767045 | |
| I0331 12:17:07.322163 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.326531 | |
| I0331 12:17:07.322178 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.92997 (* 0.3 = 0.878991 loss) | |
| I0331 12:17:07.322193 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.889532 (* 0.3 = 0.26686 loss) | |
| I0331 12:17:07.322206 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.183673 | |
| I0331 12:17:07.322217 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.767045 | |
| I0331 12:17:07.322229 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.285714 | |
| I0331 12:17:07.322242 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.90215 (* 0.3 = 0.870645 loss) | |
| I0331 12:17:07.322257 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.890859 (* 0.3 = 0.267258 loss) | |
| I0331 12:17:07.322268 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.22449 | |
| I0331 12:17:07.322280 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.767045 | |
| I0331 12:17:07.322293 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.428571 | |
| I0331 12:17:07.322305 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.69472 (* 1 = 2.69472 loss) | |
| I0331 12:17:07.322319 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.834801 (* 1 = 0.834801 loss) | |
| I0331 12:17:07.322331 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:17:07.322342 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000271263 | |
| I0331 12:17:07.322355 29371 sgd_solver.cpp:106] Iteration 28500, lr = 0.005 | |
| I0331 12:19:16.421744 29371 solver.cpp:229] Iteration 29000, loss = 5.91779 | |
| I0331 12:19:16.421890 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.170213 | |
| I0331 12:19:16.421913 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.772727 | |
| I0331 12:19:16.421926 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.319149 | |
| I0331 12:19:16.421943 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.90692 (* 0.3 = 0.872075 loss) | |
| I0331 12:19:16.421957 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.88323 (* 0.3 = 0.264969 loss) | |
| I0331 12:19:16.421970 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.212766 | |
| I0331 12:19:16.421983 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.789773 | |
| I0331 12:19:16.421994 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.361702 | |
| I0331 12:19:16.422008 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.78828 (* 0.3 = 0.836485 loss) | |
| I0331 12:19:16.422022 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.818113 (* 0.3 = 0.245434 loss) | |
| I0331 12:19:16.422034 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.191489 | |
| I0331 12:19:16.422046 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.755682 | |
| I0331 12:19:16.422058 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.489362 | |
| I0331 12:19:16.422071 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.49456 (* 1 = 2.49456 loss) | |
| I0331 12:19:16.422088 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.816798 (* 1 = 0.816798 loss) | |
| I0331 12:19:16.422101 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:19:16.422112 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000612754 | |
| I0331 12:19:16.422124 29371 sgd_solver.cpp:106] Iteration 29000, lr = 0.005 | |
| I0331 12:21:25.826736 29371 solver.cpp:229] Iteration 29500, loss = 5.85328 | |
| I0331 12:21:25.826887 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.162791 | |
| I0331 12:21:25.826908 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.784091 | |
| I0331 12:21:25.826927 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.372093 | |
| I0331 12:21:25.826942 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.65572 (* 0.3 = 0.796715 loss) | |
| I0331 12:21:25.826957 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.757823 (* 0.3 = 0.227347 loss) | |
| I0331 12:21:25.826969 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.139535 | |
| I0331 12:21:25.826982 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.767045 | |
| I0331 12:21:25.826994 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.395349 | |
| I0331 12:21:25.827008 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.66292 (* 0.3 = 0.798875 loss) | |
| I0331 12:21:25.827021 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.780585 (* 0.3 = 0.234176 loss) | |
| I0331 12:21:25.827033 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.27907 | |
| I0331 12:21:25.827045 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.818182 | |
| I0331 12:21:25.827057 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.581395 | |
| I0331 12:21:25.827080 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.40841 (* 1 = 2.40841 loss) | |
| I0331 12:21:25.827131 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.663006 (* 1 = 0.663006 loss) | |
| I0331 12:21:25.827164 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:21:25.827188 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000806462 | |
| I0331 12:21:25.827208 29371 sgd_solver.cpp:106] Iteration 29500, lr = 0.005 | |
| I0331 12:23:34.627172 29371 solver.cpp:338] Iteration 30000, Testing net (#0) | |
| I0331 12:24:04.502223 29371 solver.cpp:393] Test loss: 5.97971 | |
| I0331 12:24:04.502275 29371 solver.cpp:406] Test net output #0: loss1/accuracy = 0.101121 | |
| I0331 12:24:04.502302 29371 solver.cpp:406] Test net output #1: loss1/accuracy_incl_empty = 0.779501 | |
| I0331 12:24:04.502326 29371 solver.cpp:406] Test net output #2: loss1/accuracy_top3 = 0.309562 | |
| I0331 12:24:04.502351 29371 solver.cpp:406] Test net output #3: loss1/cross_entropy_loss = 3.79926 (* 0.3 = 1.13978 loss) | |
| I0331 12:24:04.502378 29371 solver.cpp:406] Test net output #4: loss1/cross_entropy_loss_incl_empty = 0.95043 (* 0.3 = 0.285129 loss) | |
| I0331 12:24:04.502401 29371 solver.cpp:406] Test net output #5: loss2/accuracy = 0.124875 | |
| I0331 12:24:04.502427 29371 solver.cpp:406] Test net output #6: loss2/accuracy_incl_empty = 0.784682 | |
| I0331 12:24:04.502449 29371 solver.cpp:406] Test net output #7: loss2/accuracy_top3 = 0.35136 | |
| I0331 12:24:04.502473 29371 solver.cpp:406] Test net output #8: loss2/cross_entropy_loss = 3.20875 (* 0.3 = 0.962625 loss) | |
| I0331 12:24:04.502506 29371 solver.cpp:406] Test net output #9: loss2/cross_entropy_loss_incl_empty = 0.802385 (* 0.3 = 0.240716 loss) | |
| I0331 12:24:04.502528 29371 solver.cpp:406] Test net output #10: loss3/accuracy = 0.217384 | |
| I0331 12:24:04.502550 29371 solver.cpp:406] Test net output #11: loss3/accuracy_incl_empty = 0.806409 | |
| I0331 12:24:04.502576 29371 solver.cpp:406] Test net output #12: loss3/accuracy_top3 = 0.518481 | |
| I0331 12:24:04.502600 29371 solver.cpp:406] Test net output #13: loss3/cross_entropy_loss = 2.67593 (* 1 = 2.67593 loss) | |
| I0331 12:24:04.502625 29371 solver.cpp:406] Test net output #14: loss3/cross_entropy_loss_incl_empty = 0.67554 (* 1 = 0.67554 loss) | |
| I0331 12:24:04.502646 29371 solver.cpp:406] Test net output #15: total_accuracy = 0.002 | |
| I0331 12:24:04.502667 29371 solver.cpp:406] Test net output #16: total_confidence = 0.00711783 | |
| I0331 12:24:04.655555 29371 solver.cpp:229] Iteration 30000, loss = 5.91057 | |
| I0331 12:24:04.655719 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0833333 | |
| I0331 12:24:04.655757 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.744318 | |
| I0331 12:24:04.655781 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.291667 | |
| I0331 12:24:04.655808 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.94349 (* 0.3 = 0.883048 loss) | |
| I0331 12:24:04.655835 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.892354 (* 0.3 = 0.267706 loss) | |
| I0331 12:24:04.655859 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.166667 | |
| I0331 12:24:04.655886 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.761364 | |
| I0331 12:24:04.655908 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.395833 | |
| I0331 12:24:04.655936 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.88335 (* 0.3 = 0.865004 loss) | |
| I0331 12:24:04.655971 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.865113 (* 0.3 = 0.259534 loss) | |
| I0331 12:24:04.655992 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.166667 | |
| I0331 12:24:04.656023 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.761364 | |
| I0331 12:24:04.656044 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.416667 | |
| I0331 12:24:04.656069 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.69112 (* 1 = 2.69112 loss) | |
| I0331 12:24:04.656097 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.821748 (* 1 = 0.821748 loss) | |
| I0331 12:24:04.656119 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:24:04.656139 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000213524 | |
| I0331 12:24:04.656162 29371 sgd_solver.cpp:106] Iteration 30000, lr = 0.005 | |
| I0331 12:26:13.611245 29371 solver.cpp:229] Iteration 30500, loss = 5.89275 | |
| I0331 12:26:13.611359 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.205128 | |
| I0331 12:26:13.611379 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.801136 | |
| I0331 12:26:13.611392 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.25641 | |
| I0331 12:26:13.611407 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.0066 (* 0.3 = 0.901981 loss) | |
| I0331 12:26:13.611423 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.829607 (* 0.3 = 0.248882 loss) | |
| I0331 12:26:13.611434 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.179487 | |
| I0331 12:26:13.611446 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.795455 | |
| I0331 12:26:13.611459 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.307692 | |
| I0331 12:26:13.611471 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.92507 (* 0.3 = 0.87752 loss) | |
| I0331 12:26:13.611485 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.81979 (* 0.3 = 0.245937 loss) | |
| I0331 12:26:13.611498 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.358974 | |
| I0331 12:26:13.611510 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.835227 | |
| I0331 12:26:13.611521 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.564103 | |
| I0331 12:26:13.611536 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.26415 (* 1 = 2.26415 loss) | |
| I0331 12:26:13.611548 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.604817 (* 1 = 0.604817 loss) | |
| I0331 12:26:13.611560 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:26:13.611572 29371 solver.cpp:245] Train net output #16: total_confidence = 0.00177635 | |
| I0331 12:26:13.611583 29371 sgd_solver.cpp:106] Iteration 30500, lr = 0.005 | |
| I0331 12:28:22.558701 29371 solver.cpp:229] Iteration 31000, loss = 5.83801 | |
| I0331 12:28:22.558848 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.14 | |
| I0331 12:28:22.558877 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.755682 | |
| I0331 12:28:22.558902 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.42 | |
| I0331 12:28:22.558928 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.01822 (* 0.3 = 0.905465 loss) | |
| I0331 12:28:22.558954 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.876719 (* 0.3 = 0.263016 loss) | |
| I0331 12:28:22.558977 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.14 | |
| I0331 12:28:22.559002 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.755682 | |
| I0331 12:28:22.559023 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.46 | |
| I0331 12:28:22.559049 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.87246 (* 0.3 = 0.861738 loss) | |
| I0331 12:28:22.559075 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.841918 (* 0.3 = 0.252575 loss) | |
| I0331 12:28:22.559116 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.2 | |
| I0331 12:28:22.559140 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.772727 | |
| I0331 12:28:22.559160 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.44 | |
| I0331 12:28:22.559186 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.65042 (* 1 = 2.65042 loss) | |
| I0331 12:28:22.559211 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.771782 (* 1 = 0.771782 loss) | |
| I0331 12:28:22.559232 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:28:22.559253 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000554102 | |
| I0331 12:28:22.559274 29371 sgd_solver.cpp:106] Iteration 31000, lr = 0.005 | |
| I0331 12:30:31.701535 29371 solver.cpp:229] Iteration 31500, loss = 5.826 | |
| I0331 12:30:31.701642 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.108696 | |
| I0331 12:30:31.701663 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.767045 | |
| I0331 12:30:31.701674 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.326087 | |
| I0331 12:30:31.701690 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.0958 (* 0.3 = 0.928741 loss) | |
| I0331 12:30:31.701705 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.887209 (* 0.3 = 0.266163 loss) | |
| I0331 12:30:31.701717 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.130435 | |
| I0331 12:30:31.701730 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.767045 | |
| I0331 12:30:31.701741 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.369565 | |
| I0331 12:30:31.701755 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.00263 (* 0.3 = 0.900788 loss) | |
| I0331 12:30:31.701768 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.8741 (* 0.3 = 0.26223 loss) | |
| I0331 12:30:31.701781 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.195652 | |
| I0331 12:30:31.701792 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.772727 | |
| I0331 12:30:31.701804 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.391304 | |
| I0331 12:30:31.701833 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.73061 (* 1 = 2.73061 loss) | |
| I0331 12:30:31.701848 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.773517 (* 1 = 0.773517 loss) | |
| I0331 12:30:31.701860 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:30:31.701871 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000448331 | |
| I0331 12:30:31.701886 29371 sgd_solver.cpp:106] Iteration 31500, lr = 0.005 | |
| I0331 12:32:40.712070 29371 solver.cpp:229] Iteration 32000, loss = 5.81077 | |
| I0331 12:32:40.712213 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0816327 | |
| I0331 12:32:40.712232 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.732955 | |
| I0331 12:32:40.712250 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.183673 | |
| I0331 12:32:40.712266 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.9903 (* 0.3 = 0.89709 loss) | |
| I0331 12:32:40.712281 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.906256 (* 0.3 = 0.271877 loss) | |
| I0331 12:32:40.712293 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0816327 | |
| I0331 12:32:40.712306 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.738636 | |
| I0331 12:32:40.712317 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.244898 | |
| I0331 12:32:40.712332 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.90167 (* 0.3 = 0.870501 loss) | |
| I0331 12:32:40.712345 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.873605 (* 0.3 = 0.262082 loss) | |
| I0331 12:32:40.712357 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.306122 | |
| I0331 12:32:40.712369 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.795455 | |
| I0331 12:32:40.712381 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.55102 | |
| I0331 12:32:40.712395 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.48312 (* 1 = 2.48312 loss) | |
| I0331 12:32:40.712409 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.75132 (* 1 = 0.75132 loss) | |
| I0331 12:32:40.712429 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:32:40.712441 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000457783 | |
| I0331 12:32:40.712453 29371 sgd_solver.cpp:106] Iteration 32000, lr = 0.005 | |
| I0331 12:34:49.725615 29371 solver.cpp:229] Iteration 32500, loss = 5.72218 | |
| I0331 12:34:49.725735 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.108696 | |
| I0331 12:34:49.725765 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.755682 | |
| I0331 12:34:49.725790 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.326087 | |
| I0331 12:34:49.725817 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.91419 (* 0.3 = 0.874256 loss) | |
| I0331 12:34:49.725843 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.862525 (* 0.3 = 0.258758 loss) | |
| I0331 12:34:49.725867 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.195652 | |
| I0331 12:34:49.725893 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.784091 | |
| I0331 12:34:49.725915 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.304348 | |
| I0331 12:34:49.725941 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.86462 (* 0.3 = 0.859387 loss) | |
| I0331 12:34:49.725975 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.810444 (* 0.3 = 0.243133 loss) | |
| I0331 12:34:49.725996 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.173913 | |
| I0331 12:34:49.726018 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.767045 | |
| I0331 12:34:49.726048 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.5 | |
| I0331 12:34:49.726073 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.7178 (* 1 = 2.7178 loss) | |
| I0331 12:34:49.726104 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.782867 (* 1 = 0.782867 loss) | |
| I0331 12:34:49.726125 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:34:49.726145 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000861774 | |
| I0331 12:34:49.726167 29371 sgd_solver.cpp:106] Iteration 32500, lr = 0.005 | |
| I0331 12:36:58.692569 29371 solver.cpp:229] Iteration 33000, loss = 5.77488 | |
| I0331 12:36:58.692705 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.190476 | |
| I0331 12:36:58.692735 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.789773 | |
| I0331 12:36:58.692767 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.404762 | |
| I0331 12:36:58.692798 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.74502 (* 0.3 = 0.823505 loss) | |
| I0331 12:36:58.692816 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.782477 (* 0.3 = 0.234743 loss) | |
| I0331 12:36:58.692829 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.142857 | |
| I0331 12:36:58.692842 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.784091 | |
| I0331 12:36:58.692854 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.404762 | |
| I0331 12:36:58.692867 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.76913 (* 0.3 = 0.83074 loss) | |
| I0331 12:36:58.692889 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.744396 (* 0.3 = 0.223319 loss) | |
| I0331 12:36:58.692901 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.261905 | |
| I0331 12:36:58.692914 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.806818 | |
| I0331 12:36:58.692926 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.571429 | |
| I0331 12:36:58.692948 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.41024 (* 1 = 2.41024 loss) | |
| I0331 12:36:58.692961 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.671635 (* 1 = 0.671635 loss) | |
| I0331 12:36:58.692973 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:36:58.692986 29371 solver.cpp:245] Train net output #16: total_confidence = 0.00452107 | |
| I0331 12:36:58.692997 29371 sgd_solver.cpp:106] Iteration 33000, lr = 0.005 | |
| I0331 12:39:07.728839 29371 solver.cpp:229] Iteration 33500, loss = 5.74099 | |
| I0331 12:39:07.728961 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.128205 | |
| I0331 12:39:07.728981 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.789773 | |
| I0331 12:39:07.728994 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.358974 | |
| I0331 12:39:07.729010 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.26172 (* 0.3 = 0.978516 loss) | |
| I0331 12:39:07.729024 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.857831 (* 0.3 = 0.257349 loss) | |
| I0331 12:39:07.729038 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.25641 | |
| I0331 12:39:07.729049 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.801136 | |
| I0331 12:39:07.729061 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.461538 | |
| I0331 12:39:07.729075 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.85876 (* 0.3 = 0.857627 loss) | |
| I0331 12:39:07.729091 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.828452 (* 0.3 = 0.248536 loss) | |
| I0331 12:39:07.729104 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.282051 | |
| I0331 12:39:07.729116 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.795455 | |
| I0331 12:39:07.729128 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.564103 | |
| I0331 12:39:07.729141 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.48599 (* 1 = 2.48599 loss) | |
| I0331 12:39:07.729156 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.729366 (* 1 = 0.729366 loss) | |
| I0331 12:39:07.729167 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:39:07.729179 29371 solver.cpp:245] Train net output #16: total_confidence = 0.015633 | |
| I0331 12:39:07.729194 29371 sgd_solver.cpp:106] Iteration 33500, lr = 0.005 | |
| I0331 12:41:16.840293 29371 solver.cpp:229] Iteration 34000, loss = 5.65443 | |
| I0331 12:41:16.840431 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0697674 | |
| I0331 12:41:16.840452 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.738636 | |
| I0331 12:41:16.840466 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.209302 | |
| I0331 12:41:16.840481 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.37725 (* 0.3 = 1.01318 loss) | |
| I0331 12:41:16.840495 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.98816 (* 0.3 = 0.296448 loss) | |
| I0331 12:41:16.840508 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.139535 | |
| I0331 12:41:16.840522 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.755682 | |
| I0331 12:41:16.840533 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.348837 | |
| I0331 12:41:16.840546 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.03276 (* 0.3 = 0.909827 loss) | |
| I0331 12:41:16.840560 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.934052 (* 0.3 = 0.280216 loss) | |
| I0331 12:41:16.840572 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.232558 | |
| I0331 12:41:16.840584 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.761364 | |
| I0331 12:41:16.840596 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.395349 | |
| I0331 12:41:16.840610 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.67385 (* 1 = 2.67385 loss) | |
| I0331 12:41:16.840623 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.883859 (* 1 = 0.883859 loss) | |
| I0331 12:41:16.840636 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:41:16.840646 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000252774 | |
| I0331 12:41:16.840659 29371 sgd_solver.cpp:106] Iteration 34000, lr = 0.005 | |
| I0331 12:43:25.961925 29371 solver.cpp:229] Iteration 34500, loss = 5.66662 | |
| I0331 12:43:25.962025 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.097561 | |
| I0331 12:43:25.962045 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.772727 | |
| I0331 12:43:25.962059 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.243902 | |
| I0331 12:43:25.962074 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.93541 (* 0.3 = 0.880622 loss) | |
| I0331 12:43:25.962088 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.825639 (* 0.3 = 0.247692 loss) | |
| I0331 12:43:25.962100 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.121951 | |
| I0331 12:43:25.962112 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.778409 | |
| I0331 12:43:25.962124 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.317073 | |
| I0331 12:43:25.962138 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.77733 (* 0.3 = 0.833199 loss) | |
| I0331 12:43:25.962152 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.784126 (* 0.3 = 0.235238 loss) | |
| I0331 12:43:25.962163 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.146341 | |
| I0331 12:43:25.962175 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.761364 | |
| I0331 12:43:25.962188 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.317073 | |
| I0331 12:43:25.962200 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.71156 (* 1 = 2.71156 loss) | |
| I0331 12:43:25.962214 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.802093 (* 1 = 0.802093 loss) | |
| I0331 12:43:25.962226 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:43:25.962239 29371 solver.cpp:245] Train net output #16: total_confidence = 0.00148779 | |
| I0331 12:43:25.962250 29371 sgd_solver.cpp:106] Iteration 34500, lr = 0.005 | |
| I0331 12:45:34.738037 29371 solver.cpp:338] Iteration 35000, Testing net (#0) | |
| I0331 12:46:04.546177 29371 solver.cpp:393] Test loss: 5.38048 | |
| I0331 12:46:04.546224 29371 solver.cpp:406] Test net output #0: loss1/accuracy = 0.111671 | |
| I0331 12:46:04.546241 29371 solver.cpp:406] Test net output #1: loss1/accuracy_incl_empty = 0.780091 | |
| I0331 12:46:04.546254 29371 solver.cpp:406] Test net output #2: loss1/accuracy_top3 = 0.325042 | |
| I0331 12:46:04.546269 29371 solver.cpp:406] Test net output #3: loss1/cross_entropy_loss = 3.12414 (* 0.3 = 0.937242 loss) | |
| I0331 12:46:04.546284 29371 solver.cpp:406] Test net output #4: loss1/cross_entropy_loss_incl_empty = 0.802482 (* 0.3 = 0.240745 loss) | |
| I0331 12:46:04.546296 29371 solver.cpp:406] Test net output #5: loss2/accuracy = 0.186054 | |
| I0331 12:46:04.546308 29371 solver.cpp:406] Test net output #6: loss2/accuracy_incl_empty = 0.792727 | |
| I0331 12:46:04.546319 29371 solver.cpp:406] Test net output #7: loss2/accuracy_top3 = 0.430612 | |
| I0331 12:46:04.546332 29371 solver.cpp:406] Test net output #8: loss2/cross_entropy_loss = 2.74593 (* 0.3 = 0.82378 loss) | |
| I0331 12:46:04.546346 29371 solver.cpp:406] Test net output #9: loss2/cross_entropy_loss_incl_empty = 0.74043 (* 0.3 = 0.222129 loss) | |
| I0331 12:46:04.546358 29371 solver.cpp:406] Test net output #10: loss3/accuracy = 0.293353 | |
| I0331 12:46:04.546370 29371 solver.cpp:406] Test net output #11: loss3/accuracy_incl_empty = 0.794181 | |
| I0331 12:46:04.546382 29371 solver.cpp:406] Test net output #12: loss3/accuracy_top3 = 0.568883 | |
| I0331 12:46:04.546396 29371 solver.cpp:406] Test net output #13: loss3/cross_entropy_loss = 2.42644 (* 1 = 2.42644 loss) | |
| I0331 12:46:04.546409 29371 solver.cpp:406] Test net output #14: loss3/cross_entropy_loss_incl_empty = 0.730142 (* 1 = 0.730142 loss) | |
| I0331 12:46:04.546421 29371 solver.cpp:406] Test net output #15: total_accuracy = 0 | |
| I0331 12:46:04.546432 29371 solver.cpp:406] Test net output #16: total_confidence = 0.00332237 | |
| I0331 12:46:04.698402 29371 solver.cpp:229] Iteration 35000, loss = 5.63686 | |
| I0331 12:46:04.698446 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.117647 | |
| I0331 12:46:04.698465 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.727273 | |
| I0331 12:46:04.698478 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.352941 | |
| I0331 12:46:04.698493 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.93648 (* 0.3 = 0.880945 loss) | |
| I0331 12:46:04.698508 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.956977 (* 0.3 = 0.287093 loss) | |
| I0331 12:46:04.698520 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.196078 | |
| I0331 12:46:04.698532 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.75 | |
| I0331 12:46:04.698544 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.392157 | |
| I0331 12:46:04.698559 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.81535 (* 0.3 = 0.844605 loss) | |
| I0331 12:46:04.698572 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.90261 (* 0.3 = 0.270783 loss) | |
| I0331 12:46:04.698585 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.313726 | |
| I0331 12:46:04.698596 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.784091 | |
| I0331 12:46:04.698616 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.568627 | |
| I0331 12:46:04.698637 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.49579 (* 1 = 2.49579 loss) | |
| I0331 12:46:04.698652 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.796976 (* 1 = 0.796976 loss) | |
| I0331 12:46:04.698663 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:46:04.698674 29371 solver.cpp:245] Train net output #16: total_confidence = 0.0197156 | |
| I0331 12:46:04.698690 29371 sgd_solver.cpp:106] Iteration 35000, lr = 0.005 | |
| I0331 12:48:13.778801 29371 solver.cpp:229] Iteration 35500, loss = 5.65028 | |
| I0331 12:48:13.778941 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0909091 | |
| I0331 12:48:13.778983 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.710227 | |
| I0331 12:48:13.779009 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.327273 | |
| I0331 12:48:13.779039 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.90107 (* 0.3 = 0.870322 loss) | |
| I0331 12:48:13.779057 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.962906 (* 0.3 = 0.288872 loss) | |
| I0331 12:48:13.779068 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.145455 | |
| I0331 12:48:13.779095 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.732955 | |
| I0331 12:48:13.779112 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.418182 | |
| I0331 12:48:13.779126 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.75448 (* 0.3 = 0.826343 loss) | |
| I0331 12:48:13.779140 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.895814 (* 0.3 = 0.268744 loss) | |
| I0331 12:48:13.779152 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.218182 | |
| I0331 12:48:13.779165 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.75 | |
| I0331 12:48:13.779176 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.509091 | |
| I0331 12:48:13.779191 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.45972 (* 1 = 2.45972 loss) | |
| I0331 12:48:13.779203 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.819457 (* 1 = 0.819457 loss) | |
| I0331 12:48:13.779216 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:48:13.779228 29371 solver.cpp:245] Train net output #16: total_confidence = 0.00408887 | |
| I0331 12:48:13.779240 29371 sgd_solver.cpp:106] Iteration 35500, lr = 0.005 | |
| I0331 12:50:22.816627 29371 solver.cpp:229] Iteration 36000, loss = 5.58667 | |
| I0331 12:50:22.816748 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.125 | |
| I0331 12:50:22.816772 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.75 | |
| I0331 12:50:22.816797 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.395833 | |
| I0331 12:50:22.816822 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.91216 (* 0.3 = 0.873649 loss) | |
| I0331 12:50:22.816838 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.850259 (* 0.3 = 0.255078 loss) | |
| I0331 12:50:22.816849 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.1875 | |
| I0331 12:50:22.816861 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.767045 | |
| I0331 12:50:22.816874 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.354167 | |
| I0331 12:50:22.816887 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.85303 (* 0.3 = 0.855908 loss) | |
| I0331 12:50:22.816901 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.832061 (* 0.3 = 0.249618 loss) | |
| I0331 12:50:22.816912 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.229167 | |
| I0331 12:50:22.816925 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.778409 | |
| I0331 12:50:22.816942 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.5 | |
| I0331 12:50:22.816968 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.46525 (* 1 = 2.46525 loss) | |
| I0331 12:50:22.816983 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.737888 (* 1 = 0.737888 loss) | |
| I0331 12:50:22.816995 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:50:22.817008 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000203606 | |
| I0331 12:50:22.817019 29371 sgd_solver.cpp:106] Iteration 36000, lr = 0.005 | |
| I0331 12:52:31.719971 29371 solver.cpp:229] Iteration 36500, loss = 5.56492 | |
| I0331 12:52:31.720123 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.1 | |
| I0331 12:52:31.720158 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.727273 | |
| I0331 12:52:31.720181 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.38 | |
| I0331 12:52:31.720208 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.0973 (* 0.3 = 0.929191 loss) | |
| I0331 12:52:31.720235 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.971274 (* 0.3 = 0.291382 loss) | |
| I0331 12:52:31.720257 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.14 | |
| I0331 12:52:31.720281 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.738636 | |
| I0331 12:52:31.720304 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.38 | |
| I0331 12:52:31.720329 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.1702 (* 0.3 = 0.95106 loss) | |
| I0331 12:52:31.720355 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.01105 (* 0.3 = 0.303316 loss) | |
| I0331 12:52:31.720376 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.26 | |
| I0331 12:52:31.720397 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.778409 | |
| I0331 12:52:31.720418 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.48 | |
| I0331 12:52:31.720443 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.70125 (* 1 = 2.70125 loss) | |
| I0331 12:52:31.720468 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.857953 (* 1 = 0.857953 loss) | |
| I0331 12:52:31.720489 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:52:31.720509 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000299618 | |
| I0331 12:52:31.720531 29371 sgd_solver.cpp:106] Iteration 36500, lr = 0.005 | |
| I0331 12:54:40.632700 29371 solver.cpp:229] Iteration 37000, loss = 5.53589 | |
| I0331 12:54:40.632810 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.153846 | |
| I0331 12:54:40.632830 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.75 | |
| I0331 12:54:40.632843 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.423077 | |
| I0331 12:54:40.632859 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.01618 (* 0.3 = 0.904853 loss) | |
| I0331 12:54:40.632874 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.928478 (* 0.3 = 0.278544 loss) | |
| I0331 12:54:40.632886 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.230769 | |
| I0331 12:54:40.632899 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.772727 | |
| I0331 12:54:40.632911 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.346154 | |
| I0331 12:54:40.632925 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.8897 (* 0.3 = 0.866909 loss) | |
| I0331 12:54:40.632938 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.877269 (* 0.3 = 0.263181 loss) | |
| I0331 12:54:40.632951 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.326923 | |
| I0331 12:54:40.632963 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.795455 | |
| I0331 12:54:40.632974 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.519231 | |
| I0331 12:54:40.632988 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.41936 (* 1 = 2.41936 loss) | |
| I0331 12:54:40.633005 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.744244 (* 1 = 0.744244 loss) | |
| I0331 12:54:40.633018 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:54:40.633029 29371 solver.cpp:245] Train net output #16: total_confidence = 0.0129744 | |
| I0331 12:54:40.633041 29371 sgd_solver.cpp:106] Iteration 37000, lr = 0.005 | |
| I0331 12:56:49.745440 29371 solver.cpp:229] Iteration 37500, loss = 5.46121 | |
| I0331 12:56:49.745584 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.186047 | |
| I0331 12:56:49.745604 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.795455 | |
| I0331 12:56:49.745625 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.465116 | |
| I0331 12:56:49.745640 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.69881 (* 0.3 = 0.809644 loss) | |
| I0331 12:56:49.745654 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.732574 (* 0.3 = 0.219772 loss) | |
| I0331 12:56:49.745667 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.139535 | |
| I0331 12:56:49.745679 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.767045 | |
| I0331 12:56:49.745692 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.418605 | |
| I0331 12:56:49.745707 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.75062 (* 0.3 = 0.825186 loss) | |
| I0331 12:56:49.745720 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.774306 (* 0.3 = 0.232292 loss) | |
| I0331 12:56:49.745733 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.348837 | |
| I0331 12:56:49.745744 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.829545 | |
| I0331 12:56:49.745762 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.604651 | |
| I0331 12:56:49.745795 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.10478 (* 1 = 2.10478 loss) | |
| I0331 12:56:49.745823 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.563853 (* 1 = 0.563853 loss) | |
| I0331 12:56:49.745853 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:56:49.745874 29371 solver.cpp:245] Train net output #16: total_confidence = 0.00128202 | |
| I0331 12:56:49.745898 29371 sgd_solver.cpp:106] Iteration 37500, lr = 0.005 | |
| I0331 12:58:58.637933 29371 solver.cpp:229] Iteration 38000, loss = 5.45555 | |
| I0331 12:58:58.638073 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.113208 | |
| I0331 12:58:58.638094 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.732955 | |
| I0331 12:58:58.638108 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.301887 | |
| I0331 12:58:58.638123 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.94098 (* 0.3 = 0.882293 loss) | |
| I0331 12:58:58.638137 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.900849 (* 0.3 = 0.270255 loss) | |
| I0331 12:58:58.638150 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.113208 | |
| I0331 12:58:58.638162 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.732955 | |
| I0331 12:58:58.638175 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.339623 | |
| I0331 12:58:58.638187 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.85597 (* 0.3 = 0.856793 loss) | |
| I0331 12:58:58.638201 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.882017 (* 0.3 = 0.264605 loss) | |
| I0331 12:58:58.638214 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.301887 | |
| I0331 12:58:58.638226 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.789773 | |
| I0331 12:58:58.638237 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.490566 | |
| I0331 12:58:58.638258 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.41854 (* 1 = 2.41854 loss) | |
| I0331 12:58:58.638273 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.749289 (* 1 = 0.749289 loss) | |
| I0331 12:58:58.638284 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 12:58:58.638296 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000503433 | |
| I0331 12:58:58.638309 29371 sgd_solver.cpp:106] Iteration 38000, lr = 0.005 | |
| I0331 13:01:07.546794 29371 solver.cpp:229] Iteration 38500, loss = 5.46201 | |
| I0331 13:01:07.547001 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.177778 | |
| I0331 13:01:07.547031 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.789773 | |
| I0331 13:01:07.547044 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.488889 | |
| I0331 13:01:07.547060 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.45948 (* 0.3 = 0.737845 loss) | |
| I0331 13:01:07.547075 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.681835 (* 0.3 = 0.204551 loss) | |
| I0331 13:01:07.547112 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.2 | |
| I0331 13:01:07.547125 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.795455 | |
| I0331 13:01:07.547138 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.466667 | |
| I0331 13:01:07.547158 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.35083 (* 0.3 = 0.705249 loss) | |
| I0331 13:01:07.547173 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.63832 (* 0.3 = 0.191496 loss) | |
| I0331 13:01:07.547185 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.355556 | |
| I0331 13:01:07.547197 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.835227 | |
| I0331 13:01:07.547209 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.644444 | |
| I0331 13:01:07.547222 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.92767 (* 1 = 1.92767 loss) | |
| I0331 13:01:07.547236 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.520827 (* 1 = 0.520827 loss) | |
| I0331 13:01:07.547248 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 13:01:07.547260 29371 solver.cpp:245] Train net output #16: total_confidence = 0.0097491 | |
| I0331 13:01:07.547273 29371 sgd_solver.cpp:106] Iteration 38500, lr = 0.005 | |
| I0331 13:03:16.385848 29371 solver.cpp:229] Iteration 39000, loss = 5.4072 | |
| I0331 13:03:16.385969 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.147059 | |
| I0331 13:03:16.386000 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.789773 | |
| I0331 13:03:16.386024 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.323529 | |
| I0331 13:03:16.386052 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.93531 (* 0.3 = 0.880593 loss) | |
| I0331 13:03:16.386078 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.889576 (* 0.3 = 0.266873 loss) | |
| I0331 13:03:16.386106 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.205882 | |
| I0331 13:03:16.386131 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.789773 | |
| I0331 13:03:16.386153 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.382353 | |
| I0331 13:03:16.386179 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.77231 (* 0.3 = 0.831694 loss) | |
| I0331 13:03:16.386204 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.869528 (* 0.3 = 0.260858 loss) | |
| I0331 13:03:16.386226 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.352941 | |
| I0331 13:03:16.386247 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.823864 | |
| I0331 13:03:16.386268 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.558824 | |
| I0331 13:03:16.386293 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.25911 (* 1 = 2.25911 loss) | |
| I0331 13:03:16.386319 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.670424 (* 1 = 0.670424 loss) | |
| I0331 13:03:16.386340 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 13:03:16.386363 29371 solver.cpp:245] Train net output #16: total_confidence = 0.00291117 | |
| I0331 13:03:16.386382 29371 sgd_solver.cpp:106] Iteration 39000, lr = 0.005 | |
| I0331 13:05:25.319320 29371 solver.cpp:229] Iteration 39500, loss = 5.38711 | |
| I0331 13:05:25.319552 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.177778 | |
| I0331 13:05:25.319573 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.784091 | |
| I0331 13:05:25.319586 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.4 | |
| I0331 13:05:25.319602 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.82269 (* 0.3 = 0.846806 loss) | |
| I0331 13:05:25.319617 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.782351 (* 0.3 = 0.234705 loss) | |
| I0331 13:05:25.319630 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.155556 | |
| I0331 13:05:25.319643 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.778409 | |
| I0331 13:05:25.319654 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.377778 | |
| I0331 13:05:25.319669 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.73573 (* 0.3 = 0.820719 loss) | |
| I0331 13:05:25.319682 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.743716 (* 0.3 = 0.223115 loss) | |
| I0331 13:05:25.319694 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.377778 | |
| I0331 13:05:25.319706 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.835227 | |
| I0331 13:05:25.319718 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.577778 | |
| I0331 13:05:25.319732 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.17211 (* 1 = 2.17211 loss) | |
| I0331 13:05:25.319746 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.589946 (* 1 = 0.589946 loss) | |
| I0331 13:05:25.319758 29371 solver.cpp:245] Train net output #15: total_accuracy = 0.125 | |
| I0331 13:05:25.319771 29371 solver.cpp:245] Train net output #16: total_confidence = 0.00479922 | |
| I0331 13:05:25.319783 29371 sgd_solver.cpp:106] Iteration 39500, lr = 0.005 | |
| I0331 13:07:34.081239 29371 solver.cpp:338] Iteration 40000, Testing net (#0) | |
| I0331 13:08:03.911134 29371 solver.cpp:393] Test loss: 4.75808 | |
| I0331 13:08:03.911190 29371 solver.cpp:406] Test net output #0: loss1/accuracy = 0.172732 | |
| I0331 13:08:03.911216 29371 solver.cpp:406] Test net output #1: loss1/accuracy_incl_empty = 0.794273 | |
| I0331 13:08:03.911247 29371 solver.cpp:406] Test net output #2: loss1/accuracy_top3 = 0.428678 | |
| I0331 13:08:03.911273 29371 solver.cpp:406] Test net output #3: loss1/cross_entropy_loss = 2.74806 (* 0.3 = 0.824418 loss) | |
| I0331 13:08:03.911301 29371 solver.cpp:406] Test net output #4: loss1/cross_entropy_loss_incl_empty = 0.709788 (* 0.3 = 0.212936 loss) | |
| I0331 13:08:03.911325 29371 solver.cpp:406] Test net output #5: loss2/accuracy = 0.233808 | |
| I0331 13:08:03.911347 29371 solver.cpp:406] Test net output #6: loss2/accuracy_incl_empty = 0.804227 | |
| I0331 13:08:03.911370 29371 solver.cpp:406] Test net output #7: loss2/accuracy_top3 = 0.515468 | |
| I0331 13:08:03.911393 29371 solver.cpp:406] Test net output #8: loss2/cross_entropy_loss = 2.48586 (* 0.3 = 0.745757 loss) | |
| I0331 13:08:03.911419 29371 solver.cpp:406] Test net output #9: loss2/cross_entropy_loss_incl_empty = 0.678703 (* 0.3 = 0.203611 loss) | |
| I0331 13:08:03.911440 29371 solver.cpp:406] Test net output #10: loss3/accuracy = 0.353608 | |
| I0331 13:08:03.911469 29371 solver.cpp:406] Test net output #11: loss3/accuracy_incl_empty = 0.826228 | |
| I0331 13:08:03.911490 29371 solver.cpp:406] Test net output #12: loss3/accuracy_top3 = 0.648739 | |
| I0331 13:08:03.911521 29371 solver.cpp:406] Test net output #13: loss3/cross_entropy_loss = 2.16972 (* 1 = 2.16972 loss) | |
| I0331 13:08:03.911545 29371 solver.cpp:406] Test net output #14: loss3/cross_entropy_loss_incl_empty = 0.601638 (* 1 = 0.601638 loss) | |
| I0331 13:08:03.911566 29371 solver.cpp:406] Test net output #15: total_accuracy = 0.006 | |
| I0331 13:08:03.911586 29371 solver.cpp:406] Test net output #16: total_confidence = 0.0078531 | |
| I0331 13:08:04.063030 29371 solver.cpp:229] Iteration 40000, loss = 5.39392 | |
| I0331 13:08:04.063089 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.108696 | |
| I0331 13:08:04.063140 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.75 | |
| I0331 13:08:04.063169 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.217391 | |
| I0331 13:08:04.063196 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.08495 (* 0.3 = 0.925486 loss) | |
| I0331 13:08:04.063223 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.891613 (* 0.3 = 0.267484 loss) | |
| I0331 13:08:04.063251 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.173913 | |
| I0331 13:08:04.063272 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.767045 | |
| I0331 13:08:04.063297 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.391304 | |
| I0331 13:08:04.063324 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.7802 (* 0.3 = 0.83406 loss) | |
| I0331 13:08:04.063351 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.86658 (* 0.3 = 0.259974 loss) | |
| I0331 13:08:04.063374 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.304348 | |
| I0331 13:08:04.063395 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.789773 | |
| I0331 13:08:04.063416 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.565217 | |
| I0331 13:08:04.063442 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.41976 (* 1 = 2.41976 loss) | |
| I0331 13:08:04.063467 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.734282 (* 1 = 0.734282 loss) | |
| I0331 13:08:04.063488 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 13:08:04.063509 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000350728 | |
| I0331 13:08:04.063530 29371 sgd_solver.cpp:106] Iteration 40000, lr = 0.005 | |
| I0331 13:10:12.927534 29371 solver.cpp:229] Iteration 40500, loss = 5.3804 | |
| I0331 13:10:12.927718 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.190476 | |
| I0331 13:10:12.927747 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.778409 | |
| I0331 13:10:12.927760 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.380952 | |
| I0331 13:10:12.927778 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.65428 (* 0.3 = 0.796285 loss) | |
| I0331 13:10:12.927793 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.799676 (* 0.3 = 0.239903 loss) | |
| I0331 13:10:12.927805 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.261905 | |
| I0331 13:10:12.927817 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.801136 | |
| I0331 13:10:12.927829 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.452381 | |
| I0331 13:10:12.927842 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.47725 (* 0.3 = 0.743175 loss) | |
| I0331 13:10:12.927856 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.733821 (* 0.3 = 0.220146 loss) | |
| I0331 13:10:12.927868 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.333333 | |
| I0331 13:10:12.927881 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.818182 | |
| I0331 13:10:12.927893 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.547619 | |
| I0331 13:10:12.927906 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.09337 (* 1 = 2.09337 loss) | |
| I0331 13:10:12.927920 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.603453 (* 1 = 0.603453 loss) | |
| I0331 13:10:12.927932 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 13:10:12.927944 29371 solver.cpp:245] Train net output #16: total_confidence = 0.0080738 | |
| I0331 13:10:12.927958 29371 sgd_solver.cpp:106] Iteration 40500, lr = 0.005 | |
| I0331 13:12:21.724748 29371 solver.cpp:229] Iteration 41000, loss = 5.30569 | |
| I0331 13:12:21.724915 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.122449 | |
| I0331 13:12:21.724946 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.744318 | |
| I0331 13:12:21.724967 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.22449 | |
| I0331 13:12:21.724995 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.91367 (* 0.3 = 0.874102 loss) | |
| I0331 13:12:21.725021 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.891153 (* 0.3 = 0.267346 loss) | |
| I0331 13:12:21.725042 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.163265 | |
| I0331 13:12:21.725066 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.761364 | |
| I0331 13:12:21.725090 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.306122 | |
| I0331 13:12:21.725116 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.75288 (* 0.3 = 0.825863 loss) | |
| I0331 13:12:21.725142 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.816843 (* 0.3 = 0.245053 loss) | |
| I0331 13:12:21.725163 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.265306 | |
| I0331 13:12:21.725185 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.778409 | |
| I0331 13:12:21.725206 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.489796 | |
| I0331 13:12:21.725231 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.40783 (* 1 = 2.40783 loss) | |
| I0331 13:12:21.725256 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.747992 (* 1 = 0.747992 loss) | |
| I0331 13:12:21.725283 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 13:12:21.725304 29371 solver.cpp:245] Train net output #16: total_confidence = 0.0156767 | |
| I0331 13:12:21.725327 29371 sgd_solver.cpp:106] Iteration 41000, lr = 0.005 | |
| I0331 13:14:30.950438 29371 solver.cpp:229] Iteration 41500, loss = 5.29524 | |
| I0331 13:14:30.950563 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.2 | |
| I0331 13:14:30.950583 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.784091 | |
| I0331 13:14:30.950597 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.425 | |
| I0331 13:14:30.950611 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.96211 (* 0.3 = 0.888632 loss) | |
| I0331 13:14:30.950626 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.870314 (* 0.3 = 0.261094 loss) | |
| I0331 13:14:30.950639 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.225 | |
| I0331 13:14:30.950650 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.778409 | |
| I0331 13:14:30.950662 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.5 | |
| I0331 13:14:30.950676 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.80557 (* 0.3 = 0.841672 loss) | |
| I0331 13:14:30.950690 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.849719 (* 0.3 = 0.254916 loss) | |
| I0331 13:14:30.950702 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.35 | |
| I0331 13:14:30.950714 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.818182 | |
| I0331 13:14:30.950726 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.7 | |
| I0331 13:14:30.950741 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.12044 (* 1 = 2.12044 loss) | |
| I0331 13:14:30.950754 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.627509 (* 1 = 0.627509 loss) | |
| I0331 13:14:30.950775 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 13:14:30.950786 29371 solver.cpp:245] Train net output #16: total_confidence = 0.00865234 | |
| I0331 13:14:30.950799 29371 sgd_solver.cpp:106] Iteration 41500, lr = 0.005 | |
| I0331 13:16:40.269407 29371 solver.cpp:229] Iteration 42000, loss = 5.30019 | |
| I0331 13:16:40.269538 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.170213 | |
| I0331 13:16:40.269573 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.778409 | |
| I0331 13:16:40.269608 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.404255 | |
| I0331 13:16:40.269637 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.83941 (* 0.3 = 0.851823 loss) | |
| I0331 13:16:40.269668 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.779474 (* 0.3 = 0.233842 loss) | |
| I0331 13:16:40.269695 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.191489 | |
| I0331 13:16:40.269718 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.784091 | |
| I0331 13:16:40.269740 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.489362 | |
| I0331 13:16:40.269772 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.67488 (* 0.3 = 0.802464 loss) | |
| I0331 13:16:40.269798 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.732487 (* 0.3 = 0.219746 loss) | |
| I0331 13:16:40.269825 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.276596 | |
| I0331 13:16:40.269847 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.806818 | |
| I0331 13:16:40.269868 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.638298 | |
| I0331 13:16:40.269894 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.09616 (* 1 = 2.09616 loss) | |
| I0331 13:16:40.269919 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.577424 (* 1 = 0.577424 loss) | |
| I0331 13:16:40.269942 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 13:16:40.269963 29371 solver.cpp:245] Train net output #16: total_confidence = 0.00189793 | |
| I0331 13:16:40.269984 29371 sgd_solver.cpp:106] Iteration 42000, lr = 0.005 | |
| I0331 13:18:49.289007 29371 solver.cpp:229] Iteration 42500, loss = 5.26448 | |
| I0331 13:18:49.289120 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.12963 | |
| I0331 13:18:49.289140 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.732955 | |
| I0331 13:18:49.289152 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.240741 | |
| I0331 13:18:49.289168 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.32924 (* 0.3 = 0.998771 loss) | |
| I0331 13:18:49.289183 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.04729 (* 0.3 = 0.314188 loss) | |
| I0331 13:18:49.289196 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0925926 | |
| I0331 13:18:49.289207 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.721591 | |
| I0331 13:18:49.289219 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.277778 | |
| I0331 13:18:49.289233 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.1425 (* 0.3 = 0.942749 loss) | |
| I0331 13:18:49.289247 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.989877 (* 0.3 = 0.296963 loss) | |
| I0331 13:18:49.289259 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.222222 | |
| I0331 13:18:49.289271 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.755682 | |
| I0331 13:18:49.289283 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.462963 | |
| I0331 13:18:49.289297 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.58349 (* 1 = 2.58349 loss) | |
| I0331 13:18:49.289310 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.820795 (* 1 = 0.820795 loss) | |
| I0331 13:18:49.289322 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 13:18:49.289333 29371 solver.cpp:245] Train net output #16: total_confidence = 0.000121884 | |
| I0331 13:18:49.289346 29371 sgd_solver.cpp:106] Iteration 42500, lr = 0.005 | |
| I0331 13:20:58.290822 29371 solver.cpp:229] Iteration 43000, loss = 5.18891 | |
| I0331 13:20:58.290966 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.173913 | |
| I0331 13:20:58.290987 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.767045 | |
| I0331 13:20:58.291008 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.456522 | |
| I0331 13:20:58.291023 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.66859 (* 0.3 = 0.800577 loss) | |
| I0331 13:20:58.291038 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.798773 (* 0.3 = 0.239632 loss) | |
| I0331 13:20:58.291050 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.26087 | |
| I0331 13:20:58.291062 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.801136 | |
| I0331 13:20:58.291074 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.521739 | |
| I0331 13:20:58.291108 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.67547 (* 0.3 = 0.802642 loss) | |
| I0331 13:20:58.291124 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.76563 (* 0.3 = 0.229689 loss) | |
| I0331 13:20:58.291136 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.347826 | |
| I0331 13:20:58.291148 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.806818 | |
| I0331 13:20:58.291160 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.717391 | |
| I0331 13:20:58.291174 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.01593 (* 1 = 2.01593 loss) | |
| I0331 13:20:58.291188 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.591982 (* 1 = 0.591982 loss) | |
| I0331 13:20:58.291199 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 13:20:58.291211 29371 solver.cpp:245] Train net output #16: total_confidence = 0.00409673 | |
| I0331 13:20:58.291224 29371 sgd_solver.cpp:106] Iteration 43000, lr = 0.005 | |
| I0331 13:23:07.316581 29371 solver.cpp:229] Iteration 43500, loss = 5.20925 | |
| I0331 13:23:07.316704 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.2 | |
| I0331 13:23:07.316725 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.767045 | |
| I0331 13:23:07.316736 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.38 | |
| I0331 13:23:07.316753 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.68536 (* 0.3 = 0.805607 loss) | |
| I0331 13:23:07.316768 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.819042 (* 0.3 = 0.245713 loss) | |
| I0331 13:23:07.316781 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.32 | |
| I0331 13:23:07.316792 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.789773 | |
| I0331 13:23:07.316804 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.52 | |
| I0331 13:23:07.316818 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.45619 (* 0.3 = 0.736856 loss) | |
| I0331 13:23:07.316833 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.799921 (* 0.3 = 0.239976 loss) | |
| I0331 13:23:07.316844 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.4 | |
| I0331 13:23:07.316856 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.801136 | |
| I0331 13:23:07.316869 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.6 | |
| I0331 13:23:07.316882 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.01706 (* 1 = 2.01706 loss) | |
| I0331 13:23:07.316903 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.642854 (* 1 = 0.642854 loss) | |
| I0331 13:23:07.316915 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 13:23:07.316926 29371 solver.cpp:245] Train net output #16: total_confidence = 0.00707683 | |
| I0331 13:23:07.316938 29371 sgd_solver.cpp:106] Iteration 43500, lr = 0.005 | |
| I0331 13:25:16.314532 29371 solver.cpp:229] Iteration 44000, loss = 5.19647 | |
| I0331 13:25:16.314682 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.166667 | |
| I0331 13:25:16.314702 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.772727 | |
| I0331 13:25:16.314716 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.428571 | |
| I0331 13:25:16.314733 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.70024 (* 0.3 = 0.810072 loss) | |
| I0331 13:25:16.314746 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.832567 (* 0.3 = 0.24977 loss) | |
| I0331 13:25:16.314759 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.285714 | |
| I0331 13:25:16.314771 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.801136 | |
| I0331 13:25:16.314782 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.547619 | |
| I0331 13:25:16.314796 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.36025 (* 0.3 = 0.708075 loss) | |
| I0331 13:25:16.314810 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.734002 (* 0.3 = 0.220201 loss) | |
| I0331 13:25:16.314822 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.380952 | |
| I0331 13:25:16.314834 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.818182 | |
| I0331 13:25:16.314846 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.642857 | |
| I0331 13:25:16.314859 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.05706 (* 1 = 2.05706 loss) | |
| I0331 13:25:16.314873 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.675382 (* 1 = 0.675382 loss) | |
| I0331 13:25:16.314885 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 13:25:16.314896 29371 solver.cpp:245] Train net output #16: total_confidence = 0.00403129 | |
| I0331 13:25:16.314909 29371 sgd_solver.cpp:106] Iteration 44000, lr = 0.005 | |
| I0331 13:27:25.325610 29371 solver.cpp:229] Iteration 44500, loss = 5.14168 | |
| I0331 13:27:25.325728 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.229167 | |
| I0331 13:27:25.325757 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.784091 | |
| I0331 13:27:25.325781 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.416667 | |
| I0331 13:27:25.325808 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.87106 (* 0.3 = 0.861318 loss) | |
| I0331 13:27:25.325832 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.862424 (* 0.3 = 0.258727 loss) | |
| I0331 13:27:25.325855 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.1875 | |
| I0331 13:27:25.325877 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.778409 | |
| I0331 13:27:25.325902 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.354167 | |
| I0331 13:27:25.325929 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.87489 (* 0.3 = 0.862467 loss) | |
| I0331 13:27:25.325955 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.832833 (* 0.3 = 0.24985 loss) | |
| I0331 13:27:25.325978 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.479167 | |
| I0331 13:27:25.326007 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.846591 | |
| I0331 13:27:25.326030 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.645833 | |
| I0331 13:27:25.326061 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.19622 (* 1 = 2.19622 loss) | |
| I0331 13:27:25.326086 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.630787 (* 1 = 0.630787 loss) | |
| I0331 13:27:25.326107 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 13:27:25.326128 29371 solver.cpp:245] Train net output #16: total_confidence = 0.0300244 | |
| I0331 13:27:25.326149 29371 sgd_solver.cpp:106] Iteration 44500, lr = 0.005 | |
| I0331 13:29:34.085047 29371 solver.cpp:338] Iteration 45000, Testing net (#0) | |
| I0331 13:30:03.913430 29371 solver.cpp:393] Test loss: 5.01479 | |
| I0331 13:30:03.913496 29371 solver.cpp:406] Test net output #0: loss1/accuracy = 0.164358 | |
| I0331 13:30:03.913512 29371 solver.cpp:406] Test net output #1: loss1/accuracy_incl_empty = 0.79309 | |
| I0331 13:30:03.913524 29371 solver.cpp:406] Test net output #2: loss1/accuracy_top3 = 0.418829 | |
| I0331 13:30:03.913542 29371 solver.cpp:406] Test net output #3: loss1/cross_entropy_loss = 2.84187 (* 0.3 = 0.85256 loss) | |
| I0331 13:30:03.913555 29371 solver.cpp:406] Test net output #4: loss1/cross_entropy_loss_incl_empty = 0.726923 (* 0.3 = 0.218077 loss) | |
| I0331 13:30:03.913568 29371 solver.cpp:406] Test net output #5: loss2/accuracy = 0.198907 | |
| I0331 13:30:03.913579 29371 solver.cpp:406] Test net output #6: loss2/accuracy_incl_empty = 0.802136 | |
| I0331 13:30:03.913591 29371 solver.cpp:406] Test net output #7: loss2/accuracy_top3 = 0.491042 | |
| I0331 13:30:03.913604 29371 solver.cpp:406] Test net output #8: loss2/cross_entropy_loss = 2.6961 (* 0.3 = 0.808829 loss) | |
| I0331 13:30:03.913619 29371 solver.cpp:406] Test net output #9: loss2/cross_entropy_loss_incl_empty = 0.683398 (* 0.3 = 0.205019 loss) | |
| I0331 13:30:03.913630 29371 solver.cpp:406] Test net output #10: loss3/accuracy = 0.351451 | |
| I0331 13:30:03.913642 29371 solver.cpp:406] Test net output #11: loss3/accuracy_incl_empty = 0.835501 | |
| I0331 13:30:03.913655 29371 solver.cpp:406] Test net output #12: loss3/accuracy_top3 = 0.62488 | |
| I0331 13:30:03.913671 29371 solver.cpp:406] Test net output #13: loss3/cross_entropy_loss = 2.32861 (* 1 = 2.32861 loss) | |
| I0331 13:30:03.913686 29371 solver.cpp:406] Test net output #14: loss3/cross_entropy_loss_incl_empty = 0.601692 (* 1 = 0.601692 loss) | |
| I0331 13:30:03.913697 29371 solver.cpp:406] Test net output #15: total_accuracy = 0.012 | |
| I0331 13:30:03.913710 29371 solver.cpp:406] Test net output #16: total_confidence = 0.0187454 | |
| I0331 13:30:04.066773 29371 solver.cpp:229] Iteration 45000, loss = 5.09795 | |
| I0331 13:30:04.066834 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.177778 | |
| I0331 13:30:04.066851 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.784091 | |
| I0331 13:30:04.066864 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.466667 | |
| I0331 13:30:04.066880 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.50835 (* 0.3 = 0.752504 loss) | |
| I0331 13:30:04.066895 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.697829 (* 0.3 = 0.209349 loss) | |
| I0331 13:30:04.066907 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.244444 | |
| I0331 13:30:04.066920 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.806818 | |
| I0331 13:30:04.066931 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.422222 | |
| I0331 13:30:04.066944 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.36958 (* 0.3 = 0.710873 loss) | |
| I0331 13:30:04.066958 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.642474 (* 0.3 = 0.192742 loss) | |
| I0331 13:30:04.066970 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.4 | |
| I0331 13:30:04.066983 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.835227 | |
| I0331 13:30:04.066995 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.777778 | |
| I0331 13:30:04.067008 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.81876 (* 1 = 1.81876 loss) | |
| I0331 13:30:04.067023 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.503701 (* 1 = 0.503701 loss) | |
| I0331 13:30:04.067034 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 13:30:04.067046 29371 solver.cpp:245] Train net output #16: total_confidence = 0.00234327 | |
| I0331 13:30:04.067059 29371 sgd_solver.cpp:106] Iteration 45000, lr = 0.005 | |
| I0331 13:32:13.129164 29371 solver.cpp:229] Iteration 45500, loss = 5.12126 | |
| I0331 13:32:13.129313 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.195652 | |
| I0331 13:32:13.129333 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.778409 | |
| I0331 13:32:13.129353 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.391304 | |
| I0331 13:32:13.129369 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.75493 (* 0.3 = 0.826479 loss) | |
| I0331 13:32:13.129382 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.852181 (* 0.3 = 0.255654 loss) | |
| I0331 13:32:13.129395 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.130435 | |
| I0331 13:32:13.129407 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.767045 | |
| I0331 13:32:13.129420 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.369565 | |
| I0331 13:32:13.129433 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.76736 (* 0.3 = 0.830208 loss) | |
| I0331 13:32:13.129447 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.819725 (* 0.3 = 0.245918 loss) | |
| I0331 13:32:13.129459 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.23913 | |
| I0331 13:32:13.129472 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.789773 | |
| I0331 13:32:13.129483 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.478261 | |
| I0331 13:32:13.129497 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.42488 (* 1 = 2.42488 loss) | |
| I0331 13:32:13.129510 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.692877 (* 1 = 0.692877 loss) | |
| I0331 13:32:13.129523 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 13:32:13.129534 29371 solver.cpp:245] Train net output #16: total_confidence = 0.010011 | |
| I0331 13:32:13.129546 29371 sgd_solver.cpp:106] Iteration 45500, lr = 0.005 | |
| I0331 13:34:21.979229 29371 solver.cpp:229] Iteration 46000, loss = 5.11314 | |
| I0331 13:34:21.979362 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.25 | |
| I0331 13:34:21.979382 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.778409 | |
| I0331 13:34:21.979394 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.416667 | |
| I0331 13:34:21.979409 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.75789 (* 0.3 = 0.827366 loss) | |
| I0331 13:34:21.979424 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.882047 (* 0.3 = 0.264614 loss) | |
| I0331 13:34:21.979436 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.1875 | |
| I0331 13:34:21.979455 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.761364 | |
| I0331 13:34:21.979467 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.479167 | |
| I0331 13:34:21.979481 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.72007 (* 0.3 = 0.816021 loss) | |
| I0331 13:34:21.979496 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.835127 (* 0.3 = 0.250538 loss) | |
| I0331 13:34:21.979513 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.354167 | |
| I0331 13:34:21.979526 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.801136 | |
| I0331 13:34:21.979537 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.625 | |
| I0331 13:34:21.979552 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.0663 (* 1 = 2.0663 loss) | |
| I0331 13:34:21.979565 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.645984 (* 1 = 0.645984 loss) | |
| I0331 13:34:21.979576 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 13:34:21.979588 29371 solver.cpp:245] Train net output #16: total_confidence = 0.00900507 | |
| I0331 13:34:21.979600 29371 sgd_solver.cpp:106] Iteration 46000, lr = 0.005 | |
| I0331 13:36:30.987176 29371 solver.cpp:229] Iteration 46500, loss = 5.05653 | |
| I0331 13:36:30.987342 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.166667 | |
| I0331 13:36:30.987362 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.784091 | |
| I0331 13:36:30.987382 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.277778 | |
| I0331 13:36:30.987398 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.0321 (* 0.3 = 0.909631 loss) | |
| I0331 13:36:30.987413 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.917148 (* 0.3 = 0.275144 loss) | |
| I0331 13:36:30.987426 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.166667 | |
| I0331 13:36:30.987437 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.789773 | |
| I0331 13:36:30.987449 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.388889 | |
| I0331 13:36:30.987463 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.04339 (* 0.3 = 0.913018 loss) | |
| I0331 13:36:30.987476 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.858075 (* 0.3 = 0.257423 loss) | |
| I0331 13:36:30.987488 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.277778 | |
| I0331 13:36:30.987500 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.8125 | |
| I0331 13:36:30.987512 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.472222 | |
| I0331 13:36:30.987526 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.61126 (* 1 = 2.61126 loss) | |
| I0331 13:36:30.987540 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.74808 (* 1 = 0.74808 loss) | |
| I0331 13:36:30.987560 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 13:36:30.987571 29371 solver.cpp:245] Train net output #16: total_confidence = 0.0164234 | |
| I0331 13:36:30.987583 29371 sgd_solver.cpp:106] Iteration 46500, lr = 0.005 | |
| I0331 13:38:40.556927 29371 solver.cpp:229] Iteration 47000, loss = 5.03262 | |
| I0331 13:38:40.557040 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.148936 | |
| I0331 13:38:40.557060 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.761364 | |
| I0331 13:38:40.557072 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.468085 | |
| I0331 13:38:40.557091 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.76462 (* 0.3 = 0.829386 loss) | |
| I0331 13:38:40.557109 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.802224 (* 0.3 = 0.240667 loss) | |
| I0331 13:38:40.557122 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.297872 | |
| I0331 13:38:40.557134 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.806818 | |
| I0331 13:38:40.557147 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.595745 | |
| I0331 13:38:40.557159 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.44516 (* 0.3 = 0.733548 loss) | |
| I0331 13:38:40.557174 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.722693 (* 0.3 = 0.216808 loss) | |
| I0331 13:38:40.557186 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.468085 | |
| I0331 13:38:40.557199 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.846591 | |
| I0331 13:38:40.557210 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.723404 | |
| I0331 13:38:40.557224 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.87191 (* 1 = 1.87191 loss) | |
| I0331 13:38:40.557237 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.559467 (* 1 = 0.559467 loss) | |
| I0331 13:38:40.557250 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 13:38:40.557261 29371 solver.cpp:245] Train net output #16: total_confidence = 0.0029352 | |
| I0331 13:38:40.557273 29371 sgd_solver.cpp:106] Iteration 47000, lr = 0.005 | |
| I0331 13:40:49.449348 29371 solver.cpp:229] Iteration 47500, loss = 5.04858 | |
| I0331 13:40:49.449492 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.27907 | |
| I0331 13:40:49.449513 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.806818 | |
| I0331 13:40:49.449534 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.511628 | |
| I0331 13:40:49.449550 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.51901 (* 0.3 = 0.755702 loss) | |
| I0331 13:40:49.449564 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.704053 (* 0.3 = 0.211216 loss) | |
| I0331 13:40:49.449578 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.255814 | |
| I0331 13:40:49.449589 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.801136 | |
| I0331 13:40:49.449601 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.511628 | |
| I0331 13:40:49.449615 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.45159 (* 0.3 = 0.735477 loss) | |
| I0331 13:40:49.449630 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.680367 (* 0.3 = 0.20411 loss) | |
| I0331 13:40:49.449641 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.511628 | |
| I0331 13:40:49.449653 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.869318 | |
| I0331 13:40:49.449666 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.674419 | |
| I0331 13:40:49.449681 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.7489 (* 1 = 1.7489 loss) | |
| I0331 13:40:49.449707 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.47192 (* 1 = 0.47192 loss) | |
| I0331 13:40:49.449719 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 13:40:49.449731 29371 solver.cpp:245] Train net output #16: total_confidence = 0.00196203 | |
| I0331 13:40:49.449745 29371 sgd_solver.cpp:106] Iteration 47500, lr = 0.005 | |
| I0331 13:42:58.462447 29371 solver.cpp:229] Iteration 48000, loss = 4.96852 | |
| I0331 13:42:58.462568 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.106383 | |
| I0331 13:42:58.462599 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.75 | |
| I0331 13:42:58.462622 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.361702 | |
| I0331 13:42:58.462651 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.79858 (* 0.3 = 0.839575 loss) | |
| I0331 13:42:58.462677 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.817552 (* 0.3 = 0.245266 loss) | |
| I0331 13:42:58.462702 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.234043 | |
| I0331 13:42:58.462726 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.784091 | |
| I0331 13:42:58.462749 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.382979 | |
| I0331 13:42:58.462774 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.77589 (* 0.3 = 0.832766 loss) | |
| I0331 13:42:58.462807 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.800151 (* 0.3 = 0.240045 loss) | |
| I0331 13:42:58.462829 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.446809 | |
| I0331 13:42:58.462852 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.840909 | |
| I0331 13:42:58.462880 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.659574 | |
| I0331 13:42:58.462905 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.28899 (* 1 = 2.28899 loss) | |
| I0331 13:42:58.462929 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.661347 (* 1 = 0.661347 loss) | |
| I0331 13:42:58.462951 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 13:42:58.462971 29371 solver.cpp:245] Train net output #16: total_confidence = 0.00335675 | |
| I0331 13:42:58.462993 29371 sgd_solver.cpp:106] Iteration 48000, lr = 0.005 | |
| I0331 13:45:07.430141 29371 solver.cpp:229] Iteration 48500, loss = 4.9715 | |
| I0331 13:45:07.430284 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.139535 | |
| I0331 13:45:07.430305 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.784091 | |
| I0331 13:45:07.430325 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.325581 | |
| I0331 13:45:07.430341 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.1167 (* 0.3 = 0.935011 loss) | |
| I0331 13:45:07.430356 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.827803 (* 0.3 = 0.248341 loss) | |
| I0331 13:45:07.430368 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.186047 | |
| I0331 13:45:07.430380 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.784091 | |
| I0331 13:45:07.430392 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.488372 | |
| I0331 13:45:07.430405 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.78098 (* 0.3 = 0.834293 loss) | |
| I0331 13:45:07.430419 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.77153 (* 0.3 = 0.231459 loss) | |
| I0331 13:45:07.430431 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.348837 | |
| I0331 13:45:07.430444 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.823864 | |
| I0331 13:45:07.430454 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.534884 | |
| I0331 13:45:07.430469 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.30488 (* 1 = 2.30488 loss) | |
| I0331 13:45:07.430481 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.62956 (* 1 = 0.62956 loss) | |
| I0331 13:45:07.430493 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 13:45:07.430505 29371 solver.cpp:245] Train net output #16: total_confidence = 0.011141 | |
| I0331 13:45:07.430517 29371 sgd_solver.cpp:106] Iteration 48500, lr = 0.005 | |
| I0331 13:47:16.492389 29371 solver.cpp:229] Iteration 49000, loss = 5.00834 | |
| I0331 13:47:16.492511 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.130435 | |
| I0331 13:47:16.492530 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.761364 | |
| I0331 13:47:16.492543 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.391304 | |
| I0331 13:47:16.492559 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.88582 (* 0.3 = 0.865745 loss) | |
| I0331 13:47:16.492573 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.82721 (* 0.3 = 0.248163 loss) | |
| I0331 13:47:16.492586 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.23913 | |
| I0331 13:47:16.492599 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.795455 | |
| I0331 13:47:16.492610 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.586957 | |
| I0331 13:47:16.492624 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.55852 (* 0.3 = 0.767557 loss) | |
| I0331 13:47:16.492637 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.714665 (* 0.3 = 0.2144 loss) | |
| I0331 13:47:16.492650 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.413043 | |
| I0331 13:47:16.492661 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.823864 | |
| I0331 13:47:16.492673 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.652174 | |
| I0331 13:47:16.492687 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.10952 (* 1 = 2.10952 loss) | |
| I0331 13:47:16.492700 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.628384 (* 1 = 0.628384 loss) | |
| I0331 13:47:16.492712 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 13:47:16.492724 29371 solver.cpp:245] Train net output #16: total_confidence = 0.0213996 | |
| I0331 13:47:16.492736 29371 sgd_solver.cpp:106] Iteration 49000, lr = 0.005 | |
| I0331 13:49:25.353772 29371 solver.cpp:229] Iteration 49500, loss = 4.94579 | |
| I0331 13:49:25.353926 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.102041 | |
| I0331 13:49:25.353957 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.732955 | |
| I0331 13:49:25.353981 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.346939 | |
| I0331 13:49:25.354008 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.89682 (* 0.3 = 0.869045 loss) | |
| I0331 13:49:25.354037 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.898451 (* 0.3 = 0.269535 loss) | |
| I0331 13:49:25.354063 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.22449 | |
| I0331 13:49:25.354089 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.778409 | |
| I0331 13:49:25.354110 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.489796 | |
| I0331 13:49:25.354135 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.63283 (* 0.3 = 0.789849 loss) | |
| I0331 13:49:25.354161 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.779649 (* 0.3 = 0.233895 loss) | |
| I0331 13:49:25.354184 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.408163 | |
| I0331 13:49:25.354205 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.818182 | |
| I0331 13:49:25.354226 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.673469 | |
| I0331 13:49:25.354251 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.92699 (* 1 = 1.92699 loss) | |
| I0331 13:49:25.354276 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.621433 (* 1 = 0.621433 loss) | |
| I0331 13:49:25.354298 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 13:49:25.354320 29371 solver.cpp:245] Train net output #16: total_confidence = 0.0108848 | |
| I0331 13:49:25.354342 29371 sgd_solver.cpp:106] Iteration 49500, lr = 0.005 | |
| I0331 13:51:34.121227 29371 solver.cpp:456] Snapshotting to binary proto file /mnt/snapshots/mixed_lstm9_bn_iter_50000.caffemodel | |
| I0331 13:51:34.479971 29371 sgd_solver.cpp:273] Snapshotting solver state to binary proto file /mnt/snapshots/mixed_lstm9_bn_iter_50000.solverstate | |
| I0331 13:51:34.643651 29371 solver.cpp:338] Iteration 50000, Testing net (#0) | |
| I0331 13:52:04.488386 29371 solver.cpp:393] Test loss: 4.22538 | |
| I0331 13:52:04.488497 29371 solver.cpp:406] Test net output #0: loss1/accuracy = 0.218422 | |
| I0331 13:52:04.488517 29371 solver.cpp:406] Test net output #1: loss1/accuracy_incl_empty = 0.802773 | |
| I0331 13:52:04.488529 29371 solver.cpp:406] Test net output #2: loss1/accuracy_top3 = 0.49147 | |
| I0331 13:52:04.488545 29371 solver.cpp:406] Test net output #3: loss1/cross_entropy_loss = 2.56629 (* 0.3 = 0.769886 loss) | |
| I0331 13:52:04.488560 29371 solver.cpp:406] Test net output #4: loss1/cross_entropy_loss_incl_empty = 0.681408 (* 0.3 = 0.204422 loss) | |
| I0331 13:52:04.488574 29371 solver.cpp:406] Test net output #5: loss2/accuracy = 0.263571 | |
| I0331 13:52:04.488586 29371 solver.cpp:406] Test net output #6: loss2/accuracy_incl_empty = 0.815546 | |
| I0331 13:52:04.488598 29371 solver.cpp:406] Test net output #7: loss2/accuracy_top3 = 0.586897 | |
| I0331 13:52:04.488612 29371 solver.cpp:406] Test net output #8: loss2/cross_entropy_loss = 2.35038 (* 0.3 = 0.705114 loss) | |
| I0331 13:52:04.488627 29371 solver.cpp:406] Test net output #9: loss2/cross_entropy_loss_incl_empty = 0.605716 (* 0.3 = 0.181715 loss) | |
| I0331 13:52:04.488639 29371 solver.cpp:406] Test net output #10: loss3/accuracy = 0.450717 | |
| I0331 13:52:04.488652 29371 solver.cpp:406] Test net output #11: loss3/accuracy_incl_empty = 0.85432 | |
| I0331 13:52:04.488664 29371 solver.cpp:406] Test net output #12: loss3/accuracy_top3 = 0.725485 | |
| I0331 13:52:04.488677 29371 solver.cpp:406] Test net output #13: loss3/cross_entropy_loss = 1.85952 (* 1 = 1.85952 loss) | |
| I0331 13:52:04.488692 29371 solver.cpp:406] Test net output #14: loss3/cross_entropy_loss_incl_empty = 0.504732 (* 1 = 0.504732 loss) | |
| I0331 13:52:04.488704 29371 solver.cpp:406] Test net output #15: total_accuracy = 0.025 | |
| I0331 13:52:04.488716 29371 solver.cpp:406] Test net output #16: total_confidence = 0.0226501 | |
| I0331 13:52:04.639446 29371 solver.cpp:229] Iteration 50000, loss = 4.92794 | |
| I0331 13:52:04.639494 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.27027 | |
| I0331 13:52:04.639513 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.806818 | |
| I0331 13:52:04.639525 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.405405 | |
| I0331 13:52:04.639541 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.7282 (* 0.3 = 0.81846 loss) | |
| I0331 13:52:04.639556 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.791269 (* 0.3 = 0.237381 loss) | |
| I0331 13:52:04.639569 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.189189 | |
| I0331 13:52:04.639582 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.772727 | |
| I0331 13:52:04.639595 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.486486 | |
| I0331 13:52:04.639608 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.48578 (* 0.3 = 0.745733 loss) | |
| I0331 13:52:04.639622 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.826903 (* 0.3 = 0.248071 loss) | |
| I0331 13:52:04.639637 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.324324 | |
| I0331 13:52:04.639650 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.8125 | |
| I0331 13:52:04.639663 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.459459 | |
| I0331 13:52:04.639678 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.18576 (* 1 = 2.18576 loss) | |
| I0331 13:52:04.639691 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.668048 (* 1 = 0.668048 loss) | |
| I0331 13:52:04.639704 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 13:52:04.639724 29371 solver.cpp:245] Train net output #16: total_confidence = 0.0021761 | |
| I0331 13:52:04.639736 29371 sgd_solver.cpp:106] Iteration 50000, lr = 0.005 | |
| I0331 13:54:13.553247 29371 solver.cpp:229] Iteration 50500, loss = 4.92417 | |
| I0331 13:54:13.553372 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.266667 | |
| I0331 13:54:13.553392 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.801136 | |
| I0331 13:54:13.553406 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.488889 | |
| I0331 13:54:13.553421 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.61698 (* 0.3 = 0.785094 loss) | |
| I0331 13:54:13.553436 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.763436 (* 0.3 = 0.229031 loss) | |
| I0331 13:54:13.553449 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.377778 | |
| I0331 13:54:13.553462 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.840909 | |
| I0331 13:54:13.553474 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.577778 | |
| I0331 13:54:13.553489 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.36963 (* 0.3 = 0.71089 loss) | |
| I0331 13:54:13.553503 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.64289 (* 0.3 = 0.192867 loss) | |
| I0331 13:54:13.553516 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.577778 | |
| I0331 13:54:13.553535 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.886364 | |
| I0331 13:54:13.553549 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.733333 | |
| I0331 13:54:13.553562 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.56254 (* 1 = 1.56254 loss) | |
| I0331 13:54:13.553577 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.442972 (* 1 = 0.442972 loss) | |
| I0331 13:54:13.553589 29371 solver.cpp:245] Train net output #15: total_accuracy = 0.125 | |
| I0331 13:54:13.553601 29371 solver.cpp:245] Train net output #16: total_confidence = 0.0545503 | |
| I0331 13:54:13.553614 29371 sgd_solver.cpp:106] Iteration 50500, lr = 0.005 | |
| I0331 13:56:22.554276 29371 solver.cpp:229] Iteration 51000, loss = 4.92949 | |
| I0331 13:56:22.554420 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0714286 | |
| I0331 13:56:22.554442 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.698864 | |
| I0331 13:56:22.554464 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.267857 | |
| I0331 13:56:22.554481 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.0785 (* 0.3 = 0.923551 loss) | |
| I0331 13:56:22.554496 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.02335 (* 0.3 = 0.307006 loss) | |
| I0331 13:56:22.554508 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.160714 | |
| I0331 13:56:22.554522 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.715909 | |
| I0331 13:56:22.554533 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.339286 | |
| I0331 13:56:22.554548 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.02848 (* 0.3 = 0.908545 loss) | |
| I0331 13:56:22.554561 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.03933 (* 0.3 = 0.311799 loss) | |
| I0331 13:56:22.554574 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.321429 | |
| I0331 13:56:22.554586 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.772727 | |
| I0331 13:56:22.554599 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.517857 | |
| I0331 13:56:22.554612 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.40854 (* 1 = 2.40854 loss) | |
| I0331 13:56:22.554626 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.813587 (* 1 = 0.813587 loss) | |
| I0331 13:56:22.554638 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 13:56:22.554651 29371 solver.cpp:245] Train net output #16: total_confidence = 0.0121725 | |
| I0331 13:56:22.554662 29371 sgd_solver.cpp:106] Iteration 51000, lr = 0.005 | |
| I0331 13:58:31.398998 29371 solver.cpp:229] Iteration 51500, loss = 4.78701 | |
| I0331 13:58:31.399149 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.288889 | |
| I0331 13:58:31.399178 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.801136 | |
| I0331 13:58:31.399199 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.511111 | |
| I0331 13:58:31.399227 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.44643 (* 0.3 = 0.733929 loss) | |
| I0331 13:58:31.399253 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.715411 (* 0.3 = 0.214623 loss) | |
| I0331 13:58:31.399276 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.355556 | |
| I0331 13:58:31.399299 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.829545 | |
| I0331 13:58:31.399322 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.577778 | |
| I0331 13:58:31.399348 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.187 (* 0.3 = 0.656099 loss) | |
| I0331 13:58:31.399372 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.620507 (* 0.3 = 0.186152 loss) | |
| I0331 13:58:31.399399 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.511111 | |
| I0331 13:58:31.399421 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.869318 | |
| I0331 13:58:31.399443 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.822222 | |
| I0331 13:58:31.399469 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.49285 (* 1 = 1.49285 loss) | |
| I0331 13:58:31.399494 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.414822 (* 1 = 0.414822 loss) | |
| I0331 13:58:31.399516 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 13:58:31.399538 29371 solver.cpp:245] Train net output #16: total_confidence = 0.0278136 | |
| I0331 13:58:31.399559 29371 sgd_solver.cpp:106] Iteration 51500, lr = 0.005 | |
| I0331 14:00:40.523910 29371 solver.cpp:229] Iteration 52000, loss = 4.86122 | |
| I0331 14:00:40.524036 29371 solver.cpp:245] Train net output #0: loss1/accuracy = 0.22 | |
| I0331 14:00:40.524057 29371 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.767045 | |
| I0331 14:00:40.524070 29371 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.42 | |
| I0331 14:00:40.524086 29371 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.42168 (* 0.3 = 1.0265 loss) | |
| I0331 14:00:40.524101 29371 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.02074 (* 0.3 = 0.306223 loss) | |
| I0331 14:00:40.524114 29371 solver.cpp:245] Train net output #5: loss2/accuracy = 0.28 | |
| I0331 14:00:40.524127 29371 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.778409 | |
| I0331 14:00:40.524139 29371 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.46 | |
| I0331 14:00:40.524153 29371 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.36284 (* 0.3 = 1.00885 loss) | |
| I0331 14:00:40.524168 29371 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.02121 (* 0.3 = 0.306363 loss) | |
| I0331 14:00:40.524180 29371 solver.cpp:245] Train net output #10: loss3/accuracy = 0.36 | |
| I0331 14:00:40.524193 29371 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.806818 | |
| I0331 14:00:40.524204 29371 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.64 | |
| I0331 14:00:40.524219 29371 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.94014 (* 1 = 2.94014 loss) | |
| I0331 14:00:40.524232 29371 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.877003 (* 1 = 0.877003 loss) | |
| I0331 14:00:40.524245 29371 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:00:40.524256 29371 solver.cpp:245] Train net output #16: total_confidence = 0.0147455 | |
| I0331 14:00:40.524269 29371 sgd_solver.cpp:106] Iteration 52000, lr = 0.005 | |
| I0331 14:01:41.565475 29371 solver.cpp:456] Snapshotting to binary proto file /mnt/snapshots/mixed_lstm9_bn_iter_52237.caffemodel | |
| I0331 14:01:41.862465 29371 sgd_solver.cpp:273] Snapshotting solver state to binary proto file /mnt/snapshots/mixed_lstm9_bn_iter_52237.solverstate | |
| I0331 14:01:42.025131 29371 solver.cpp:302] Optimization stopped early. | |
| I0331 14:01:42.025187 29371 caffe.cpp:222] Optimization Done. | |
| I0331 14:02:47.620702 30833 solver.cpp:280] Solving mixed_lstm | |
| I0331 14:02:47.620714 30833 solver.cpp:281] Learning Rate Policy: fixed | |
| I0331 14:02:47.971550 30833 solver.cpp:229] Iteration 0, loss = 4.24602 | |
| I0331 14:02:47.971597 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.146341 | |
| I0331 14:02:47.971614 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.755682 | |
| I0331 14:02:47.971627 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.439024 | |
| I0331 14:02:47.971647 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.52419 (* 0.3 = 0.757257 loss) | |
| I0331 14:02:47.971662 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.836962 (* 0.3 = 0.251089 loss) | |
| I0331 14:02:47.971701 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.195122 | |
| I0331 14:02:47.971716 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.767045 | |
| I0331 14:02:47.971729 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.512195 | |
| I0331 14:02:47.971742 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.42359 (* 0.3 = 0.727077 loss) | |
| I0331 14:02:47.971756 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.784851 (* 0.3 = 0.235455 loss) | |
| I0331 14:02:47.971768 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.390244 | |
| I0331 14:02:47.971779 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.818182 | |
| I0331 14:02:47.971792 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.780488 | |
| I0331 14:02:47.971807 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.70794 (* 1 = 1.70794 loss) | |
| I0331 14:02:47.971820 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.567192 (* 1 = 0.567192 loss) | |
| I0331 14:02:47.971832 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:02:47.971843 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0169351 | |
| I0331 14:02:47.971861 30833 sgd_solver.cpp:106] Iteration 0, lr = 0.05 | |
| I0331 14:04:56.378499 30833 solver.cpp:229] Iteration 500, loss = 6.64907 | |
| I0331 14:04:56.378809 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.111111 | |
| I0331 14:04:56.378829 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.755682 | |
| I0331 14:04:56.378842 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.244444 | |
| I0331 14:04:56.378857 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.14804 (* 0.3 = 0.944412 loss) | |
| I0331 14:04:56.378872 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.954351 (* 0.3 = 0.286305 loss) | |
| I0331 14:04:56.378885 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.133333 | |
| I0331 14:04:56.378897 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.744318 | |
| I0331 14:04:56.378908 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.311111 | |
| I0331 14:04:56.378921 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.04441 (* 0.3 = 0.913322 loss) | |
| I0331 14:04:56.378936 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.94686 (* 0.3 = 0.284058 loss) | |
| I0331 14:04:56.378947 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.177778 | |
| I0331 14:04:56.378958 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.761364 | |
| I0331 14:04:56.378970 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.4 | |
| I0331 14:04:56.378983 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.66199 (* 1 = 2.66199 loss) | |
| I0331 14:04:56.378998 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.809095 (* 1 = 0.809095 loss) | |
| I0331 14:04:56.379009 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:04:56.379020 30833 solver.cpp:245] Train net output #16: total_confidence = 0.000294867 | |
| I0331 14:04:56.379032 30833 sgd_solver.cpp:106] Iteration 500, lr = 0.05 | |
| I0331 14:07:04.796340 30833 solver.cpp:229] Iteration 1000, loss = 6.09704 | |
| I0331 14:07:04.796499 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0681818 | |
| I0331 14:07:04.796519 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.75 | |
| I0331 14:07:04.796532 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.272727 | |
| I0331 14:07:04.796548 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.40946 (* 0.3 = 1.02284 loss) | |
| I0331 14:07:04.796563 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.967074 (* 0.3 = 0.290122 loss) | |
| I0331 14:07:04.796576 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.204545 | |
| I0331 14:07:04.796587 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.772727 | |
| I0331 14:07:04.796599 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.363636 | |
| I0331 14:07:04.796613 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.11236 (* 0.3 = 0.933709 loss) | |
| I0331 14:07:04.796627 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.949143 (* 0.3 = 0.284743 loss) | |
| I0331 14:07:04.796638 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.227273 | |
| I0331 14:07:04.796653 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.784091 | |
| I0331 14:07:04.796665 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.522727 | |
| I0331 14:07:04.796679 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.90443 (* 1 = 2.90443 loss) | |
| I0331 14:07:04.796692 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.818631 (* 1 = 0.818631 loss) | |
| I0331 14:07:04.796705 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:07:04.796716 30833 solver.cpp:245] Train net output #16: total_confidence = 0.000550399 | |
| I0331 14:07:04.796728 30833 sgd_solver.cpp:106] Iteration 1000, lr = 0.05 | |
| I0331 14:09:13.289876 30833 solver.cpp:229] Iteration 1500, loss = 5.92157 | |
| I0331 14:09:13.289991 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.113636 | |
| I0331 14:09:13.290011 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.767045 | |
| I0331 14:09:13.290024 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.295455 | |
| I0331 14:09:13.290040 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.77568 (* 0.3 = 1.13271 loss) | |
| I0331 14:09:13.290055 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.03922 (* 0.3 = 0.311767 loss) | |
| I0331 14:09:13.290066 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.113636 | |
| I0331 14:09:13.290078 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.761364 | |
| I0331 14:09:13.290091 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.340909 | |
| I0331 14:09:13.290107 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.365 (* 0.3 = 1.0095 loss) | |
| I0331 14:09:13.290120 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.910731 (* 0.3 = 0.273219 loss) | |
| I0331 14:09:13.290132 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.204545 | |
| I0331 14:09:13.290144 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.778409 | |
| I0331 14:09:13.290156 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.477273 | |
| I0331 14:09:13.290170 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.9549 (* 1 = 2.9549 loss) | |
| I0331 14:09:13.290184 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.825655 (* 1 = 0.825655 loss) | |
| I0331 14:09:13.290195 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:09:13.290206 30833 solver.cpp:245] Train net output #16: total_confidence = 0.00292817 | |
| I0331 14:09:13.290218 30833 sgd_solver.cpp:106] Iteration 1500, lr = 0.05 | |
| I0331 14:11:21.636018 30833 solver.cpp:229] Iteration 2000, loss = 5.82502 | |
| I0331 14:11:21.636174 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0512821 | |
| I0331 14:11:21.636195 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.761364 | |
| I0331 14:11:21.636217 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.205128 | |
| I0331 14:11:21.636234 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.15539 (* 0.3 = 0.946617 loss) | |
| I0331 14:11:21.636247 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.838046 (* 0.3 = 0.251414 loss) | |
| I0331 14:11:21.636260 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0512821 | |
| I0331 14:11:21.636271 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.767045 | |
| I0331 14:11:21.636283 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.25641 | |
| I0331 14:11:21.636296 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.15354 (* 0.3 = 0.946062 loss) | |
| I0331 14:11:21.636310 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.874854 (* 0.3 = 0.262456 loss) | |
| I0331 14:11:21.636322 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.153846 | |
| I0331 14:11:21.636334 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.761364 | |
| I0331 14:11:21.636346 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.358974 | |
| I0331 14:11:21.636360 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.96532 (* 1 = 2.96532 loss) | |
| I0331 14:11:21.636373 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.880641 (* 1 = 0.880641 loss) | |
| I0331 14:11:21.636385 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:11:21.636396 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0150364 | |
| I0331 14:11:21.636409 30833 sgd_solver.cpp:106] Iteration 2000, lr = 0.05 | |
| I0331 14:13:30.012887 30833 solver.cpp:229] Iteration 2500, loss = 5.67648 | |
| I0331 14:13:30.013020 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.159091 | |
| I0331 14:13:30.013041 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.778409 | |
| I0331 14:13:30.013053 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.363636 | |
| I0331 14:13:30.013069 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.83164 (* 0.3 = 0.849492 loss) | |
| I0331 14:13:30.013087 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.841017 (* 0.3 = 0.252305 loss) | |
| I0331 14:13:30.013100 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.159091 | |
| I0331 14:13:30.013113 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.767045 | |
| I0331 14:13:30.013124 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.340909 | |
| I0331 14:13:30.013139 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.70749 (* 0.3 = 0.812248 loss) | |
| I0331 14:13:30.013151 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.864661 (* 0.3 = 0.259398 loss) | |
| I0331 14:13:30.013164 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.386364 | |
| I0331 14:13:30.013175 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.835227 | |
| I0331 14:13:30.013187 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.659091 | |
| I0331 14:13:30.013201 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.93313 (* 1 = 1.93313 loss) | |
| I0331 14:13:30.013216 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.591129 (* 1 = 0.591129 loss) | |
| I0331 14:13:30.013226 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:13:30.013238 30833 solver.cpp:245] Train net output #16: total_confidence = 0.00360238 | |
| I0331 14:13:30.013250 30833 sgd_solver.cpp:106] Iteration 2500, lr = 0.05 | |
| I0331 14:15:38.385095 30833 solver.cpp:229] Iteration 3000, loss = 5.46103 | |
| I0331 14:15:38.385236 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.104167 | |
| I0331 14:15:38.385256 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.727273 | |
| I0331 14:15:38.385277 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.291667 | |
| I0331 14:15:38.385293 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.949 (* 0.3 = 0.8847 loss) | |
| I0331 14:15:38.385306 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.02765 (* 0.3 = 0.308294 loss) | |
| I0331 14:15:38.385318 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.25 | |
| I0331 14:15:38.385330 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.761364 | |
| I0331 14:15:38.385342 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.416667 | |
| I0331 14:15:38.385355 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.84522 (* 0.3 = 0.853566 loss) | |
| I0331 14:15:38.385370 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.939056 (* 0.3 = 0.281717 loss) | |
| I0331 14:15:38.385380 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.229167 | |
| I0331 14:15:38.385392 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.772727 | |
| I0331 14:15:38.385404 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.4375 | |
| I0331 14:15:38.385417 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.44687 (* 1 = 2.44687 loss) | |
| I0331 14:15:38.385431 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.77577 (* 1 = 0.77577 loss) | |
| I0331 14:15:38.385442 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:15:38.385453 30833 solver.cpp:245] Train net output #16: total_confidence = 0.00365073 | |
| I0331 14:15:38.385465 30833 sgd_solver.cpp:106] Iteration 3000, lr = 0.05 | |
| I0331 14:17:46.717217 30833 solver.cpp:229] Iteration 3500, loss = 5.39617 | |
| I0331 14:17:46.717334 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.113636 | |
| I0331 14:17:46.717353 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.767045 | |
| I0331 14:17:46.717366 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.5 | |
| I0331 14:17:46.717382 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.71555 (* 0.3 = 0.814666 loss) | |
| I0331 14:17:46.717396 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.726761 (* 0.3 = 0.218028 loss) | |
| I0331 14:17:46.717409 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.227273 | |
| I0331 14:17:46.717422 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.789773 | |
| I0331 14:17:46.717433 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.363636 | |
| I0331 14:17:46.717447 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.67775 (* 0.3 = 0.803324 loss) | |
| I0331 14:17:46.717459 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.733304 (* 0.3 = 0.219991 loss) | |
| I0331 14:17:46.717471 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.340909 | |
| I0331 14:17:46.717483 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.823864 | |
| I0331 14:17:46.717494 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.659091 | |
| I0331 14:17:46.717509 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.89085 (* 1 = 1.89085 loss) | |
| I0331 14:17:46.717521 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.502916 (* 1 = 0.502916 loss) | |
| I0331 14:17:46.717533 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:17:46.717545 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0171254 | |
| I0331 14:17:46.717556 30833 sgd_solver.cpp:106] Iteration 3500, lr = 0.05 | |
| I0331 14:19:55.053354 30833 solver.cpp:229] Iteration 4000, loss = 5.33029 | |
| I0331 14:19:55.053510 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.23913 | |
| I0331 14:19:55.053532 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.784091 | |
| I0331 14:19:55.053553 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.413043 | |
| I0331 14:19:55.053573 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.73323 (* 0.3 = 0.819969 loss) | |
| I0331 14:19:55.053602 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.824063 (* 0.3 = 0.247219 loss) | |
| I0331 14:19:55.053617 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.304348 | |
| I0331 14:19:55.053630 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.789773 | |
| I0331 14:19:55.053642 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.543478 | |
| I0331 14:19:55.053655 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.51275 (* 0.3 = 0.753826 loss) | |
| I0331 14:19:55.053669 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.778477 (* 0.3 = 0.233543 loss) | |
| I0331 14:19:55.053684 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.434783 | |
| I0331 14:19:55.053697 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.829545 | |
| I0331 14:19:55.053709 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.652174 | |
| I0331 14:19:55.053722 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.01767 (* 1 = 2.01767 loss) | |
| I0331 14:19:55.053736 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.613835 (* 1 = 0.613835 loss) | |
| I0331 14:19:55.053748 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:19:55.053760 30833 solver.cpp:245] Train net output #16: total_confidence = 0.00748734 | |
| I0331 14:19:55.053771 30833 sgd_solver.cpp:106] Iteration 4000, lr = 0.05 | |
| I0331 14:22:03.480247 30833 solver.cpp:229] Iteration 4500, loss = 5.28591 | |
| I0331 14:22:03.480365 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0677966 | |
| I0331 14:22:03.480384 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.676136 | |
| I0331 14:22:03.480397 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.338983 | |
| I0331 14:22:03.480412 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.06984 (* 0.3 = 0.920952 loss) | |
| I0331 14:22:03.480427 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.08385 (* 0.3 = 0.325156 loss) | |
| I0331 14:22:03.480439 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.118644 | |
| I0331 14:22:03.480451 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.698864 | |
| I0331 14:22:03.480468 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.355932 | |
| I0331 14:22:03.480492 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.14063 (* 0.3 = 0.942189 loss) | |
| I0331 14:22:03.480509 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.08472 (* 0.3 = 0.325417 loss) | |
| I0331 14:22:03.480520 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.288136 | |
| I0331 14:22:03.480532 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.755682 | |
| I0331 14:22:03.480545 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.457627 | |
| I0331 14:22:03.480557 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.62995 (* 1 = 2.62995 loss) | |
| I0331 14:22:03.480571 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.897101 (* 1 = 0.897101 loss) | |
| I0331 14:22:03.480583 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:22:03.480594 30833 solver.cpp:245] Train net output #16: total_confidence = 0.00121279 | |
| I0331 14:22:03.480607 30833 sgd_solver.cpp:106] Iteration 4500, lr = 0.05 | |
| I0331 14:24:11.670492 30833 solver.cpp:338] Iteration 5000, Testing net (#0) | |
| I0331 14:24:41.475078 30833 solver.cpp:393] Test loss: 6.73922 | |
| I0331 14:24:41.475137 30833 solver.cpp:406] Test net output #0: loss1/accuracy = 0.0846785 | |
| I0331 14:24:41.475153 30833 solver.cpp:406] Test net output #1: loss1/accuracy_incl_empty = 0.767636 | |
| I0331 14:24:41.475165 30833 solver.cpp:406] Test net output #2: loss1/accuracy_top3 = 0.215428 | |
| I0331 14:24:41.475180 30833 solver.cpp:406] Test net output #3: loss1/cross_entropy_loss = 3.87344 (* 0.3 = 1.16203 loss) | |
| I0331 14:24:41.475194 30833 solver.cpp:406] Test net output #4: loss1/cross_entropy_loss_incl_empty = 1.01342 (* 0.3 = 0.304026 loss) | |
| I0331 14:24:41.475208 30833 solver.cpp:406] Test net output #5: loss2/accuracy = 0.151448 | |
| I0331 14:24:41.475219 30833 solver.cpp:406] Test net output #6: loss2/accuracy_incl_empty = 0.783818 | |
| I0331 14:24:41.475230 30833 solver.cpp:406] Test net output #7: loss2/accuracy_top3 = 0.309599 | |
| I0331 14:24:41.475244 30833 solver.cpp:406] Test net output #8: loss2/cross_entropy_loss = 3.57977 (* 0.3 = 1.07393 loss) | |
| I0331 14:24:41.475257 30833 solver.cpp:406] Test net output #9: loss2/cross_entropy_loss_incl_empty = 0.92941 (* 0.3 = 0.278823 loss) | |
| I0331 14:24:41.475268 30833 solver.cpp:406] Test net output #10: loss3/accuracy = 0.265756 | |
| I0331 14:24:41.475281 30833 solver.cpp:406] Test net output #11: loss3/accuracy_incl_empty = 0.796364 | |
| I0331 14:24:41.475291 30833 solver.cpp:406] Test net output #12: loss3/accuracy_top3 = 0.470356 | |
| I0331 14:24:41.475304 30833 solver.cpp:406] Test net output #13: loss3/cross_entropy_loss = 3.07264 (* 1 = 3.07264 loss) | |
| I0331 14:24:41.475318 30833 solver.cpp:406] Test net output #14: loss3/cross_entropy_loss_incl_empty = 0.847765 (* 1 = 0.847765 loss) | |
| I0331 14:24:41.475330 30833 solver.cpp:406] Test net output #15: total_accuracy = 0.006 | |
| I0331 14:24:41.475342 30833 solver.cpp:406] Test net output #16: total_confidence = 0.012321 | |
| I0331 14:24:41.625422 30833 solver.cpp:229] Iteration 5000, loss = 5.21903 | |
| I0331 14:24:41.625468 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.255319 | |
| I0331 14:24:41.625483 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.789773 | |
| I0331 14:24:41.625496 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.404255 | |
| I0331 14:24:41.625511 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.86535 (* 0.3 = 0.859606 loss) | |
| I0331 14:24:41.625525 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.823656 (* 0.3 = 0.247097 loss) | |
| I0331 14:24:41.625538 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.0851064 | |
| I0331 14:24:41.625551 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.75 | |
| I0331 14:24:41.625563 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.361702 | |
| I0331 14:24:41.625577 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.89942 (* 0.3 = 0.869827 loss) | |
| I0331 14:24:41.625591 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.833443 (* 0.3 = 0.250033 loss) | |
| I0331 14:24:41.625607 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.297872 | |
| I0331 14:24:41.625624 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.789773 | |
| I0331 14:24:41.625644 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.531915 | |
| I0331 14:24:41.625658 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.39149 (* 1 = 2.39149 loss) | |
| I0331 14:24:41.625672 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.724027 (* 1 = 0.724027 loss) | |
| I0331 14:24:41.625684 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:24:41.625704 30833 solver.cpp:245] Train net output #16: total_confidence = 0.000678832 | |
| I0331 14:24:41.625715 30833 sgd_solver.cpp:106] Iteration 5000, lr = 0.05 | |
| I0331 14:26:50.026554 30833 solver.cpp:229] Iteration 5500, loss = 5.15018 | |
| I0331 14:26:50.026700 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.227273 | |
| I0331 14:26:50.026720 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.795455 | |
| I0331 14:26:50.026732 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.454545 | |
| I0331 14:26:50.026749 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.59752 (* 0.3 = 0.779257 loss) | |
| I0331 14:26:50.026763 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.739084 (* 0.3 = 0.221725 loss) | |
| I0331 14:26:50.026777 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.25 | |
| I0331 14:26:50.026789 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.801136 | |
| I0331 14:26:50.026801 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.522727 | |
| I0331 14:26:50.026814 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.52681 (* 0.3 = 0.758042 loss) | |
| I0331 14:26:50.026829 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.723596 (* 0.3 = 0.217079 loss) | |
| I0331 14:26:50.026840 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.454545 | |
| I0331 14:26:50.026852 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.852273 | |
| I0331 14:26:50.026865 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.659091 | |
| I0331 14:26:50.026878 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.92305 (* 1 = 1.92305 loss) | |
| I0331 14:26:50.026891 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.555217 (* 1 = 0.555217 loss) | |
| I0331 14:26:50.026903 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.125 | |
| I0331 14:26:50.026916 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0135831 | |
| I0331 14:26:50.026927 30833 sgd_solver.cpp:106] Iteration 5500, lr = 0.05 | |
| I0331 14:28:58.305781 30833 solver.cpp:229] Iteration 6000, loss = 5.08182 | |
| I0331 14:28:58.305903 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.148936 | |
| I0331 14:28:58.305923 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.755682 | |
| I0331 14:28:58.305937 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.382979 | |
| I0331 14:28:58.305953 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.96292 (* 0.3 = 0.888877 loss) | |
| I0331 14:28:58.305966 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.910554 (* 0.3 = 0.273166 loss) | |
| I0331 14:28:58.305979 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.191489 | |
| I0331 14:28:58.305991 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.778409 | |
| I0331 14:28:58.306002 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.297872 | |
| I0331 14:28:58.306016 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.89445 (* 0.3 = 0.868336 loss) | |
| I0331 14:28:58.306030 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.849366 (* 0.3 = 0.25481 loss) | |
| I0331 14:28:58.306042 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.276596 | |
| I0331 14:28:58.306054 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.806818 | |
| I0331 14:28:58.306066 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.468085 | |
| I0331 14:28:58.306079 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.36271 (* 1 = 2.36271 loss) | |
| I0331 14:28:58.306107 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.668872 (* 1 = 0.668872 loss) | |
| I0331 14:28:58.306120 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:28:58.306133 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0257377 | |
| I0331 14:28:58.306144 30833 sgd_solver.cpp:106] Iteration 6000, lr = 0.05 | |
| I0331 14:31:06.645843 30833 solver.cpp:229] Iteration 6500, loss = 5.03548 | |
| I0331 14:31:06.645992 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.22449 | |
| I0331 14:31:06.646011 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.784091 | |
| I0331 14:31:06.646023 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.367347 | |
| I0331 14:31:06.646045 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.02935 (* 0.3 = 0.908806 loss) | |
| I0331 14:31:06.646059 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.878445 (* 0.3 = 0.263533 loss) | |
| I0331 14:31:06.646072 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.306122 | |
| I0331 14:31:06.646087 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.806818 | |
| I0331 14:31:06.646100 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.469388 | |
| I0331 14:31:06.646113 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.03402 (* 0.3 = 0.910205 loss) | |
| I0331 14:31:06.646126 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.886855 (* 0.3 = 0.266057 loss) | |
| I0331 14:31:06.646138 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.408163 | |
| I0331 14:31:06.646150 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.823864 | |
| I0331 14:31:06.646162 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.591837 | |
| I0331 14:31:06.646175 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.42876 (* 1 = 2.42876 loss) | |
| I0331 14:31:06.646189 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.717023 (* 1 = 0.717023 loss) | |
| I0331 14:31:06.646201 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:31:06.646214 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0177702 | |
| I0331 14:31:06.646225 30833 sgd_solver.cpp:106] Iteration 6500, lr = 0.05 | |
| I0331 14:33:14.989632 30833 solver.cpp:229] Iteration 7000, loss = 4.91872 | |
| I0331 14:33:14.989756 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.26 | |
| I0331 14:33:14.989775 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.789773 | |
| I0331 14:33:14.989787 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.4 | |
| I0331 14:33:14.989804 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.80566 (* 0.3 = 0.841699 loss) | |
| I0331 14:33:14.989819 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.822797 (* 0.3 = 0.246839 loss) | |
| I0331 14:33:14.989831 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.24 | |
| I0331 14:33:14.989843 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.778409 | |
| I0331 14:33:14.989856 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.48 | |
| I0331 14:33:14.989868 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.73416 (* 0.3 = 0.820249 loss) | |
| I0331 14:33:14.989882 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.810427 (* 0.3 = 0.243128 loss) | |
| I0331 14:33:14.989894 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.26 | |
| I0331 14:33:14.989905 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.778409 | |
| I0331 14:33:14.989917 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.54 | |
| I0331 14:33:14.989931 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.41686 (* 1 = 2.41686 loss) | |
| I0331 14:33:14.989945 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.746085 (* 1 = 0.746085 loss) | |
| I0331 14:33:14.989964 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:33:14.989975 30833 solver.cpp:245] Train net output #16: total_confidence = 0.00851621 | |
| I0331 14:33:14.989987 30833 sgd_solver.cpp:106] Iteration 7000, lr = 0.05 | |
| I0331 14:35:23.233705 30833 solver.cpp:229] Iteration 7500, loss = 4.89486 | |
| I0331 14:35:23.233850 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.191489 | |
| I0331 14:35:23.233871 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.761364 | |
| I0331 14:35:23.233892 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.510638 | |
| I0331 14:35:23.233908 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.44819 (* 0.3 = 0.734457 loss) | |
| I0331 14:35:23.233923 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.750568 (* 0.3 = 0.22517 loss) | |
| I0331 14:35:23.233935 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.319149 | |
| I0331 14:35:23.233948 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.784091 | |
| I0331 14:35:23.233959 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.595745 | |
| I0331 14:35:23.233973 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.23208 (* 0.3 = 0.669625 loss) | |
| I0331 14:35:23.233989 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.730046 (* 0.3 = 0.219014 loss) | |
| I0331 14:35:23.234000 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.489362 | |
| I0331 14:35:23.234011 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.846591 | |
| I0331 14:35:23.234030 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.787234 | |
| I0331 14:35:23.234043 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.59095 (* 1 = 1.59095 loss) | |
| I0331 14:35:23.234057 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.499945 (* 1 = 0.499945 loss) | |
| I0331 14:35:23.234069 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:35:23.234091 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0246471 | |
| I0331 14:35:23.234103 30833 sgd_solver.cpp:106] Iteration 7500, lr = 0.05 | |
| I0331 14:37:31.633882 30833 solver.cpp:229] Iteration 8000, loss = 4.85201 | |
| I0331 14:37:31.634009 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.227273 | |
| I0331 14:37:31.634030 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.801136 | |
| I0331 14:37:31.634043 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.318182 | |
| I0331 14:37:31.634059 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.00128 (* 0.3 = 0.900384 loss) | |
| I0331 14:37:31.634073 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.836002 (* 0.3 = 0.250801 loss) | |
| I0331 14:37:31.634088 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.181818 | |
| I0331 14:37:31.634109 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.778409 | |
| I0331 14:37:31.634120 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.477273 | |
| I0331 14:37:31.634135 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.84064 (* 0.3 = 0.852193 loss) | |
| I0331 14:37:31.634148 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.798208 (* 0.3 = 0.239462 loss) | |
| I0331 14:37:31.634166 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.204545 | |
| I0331 14:37:31.634177 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.789773 | |
| I0331 14:37:31.634188 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.454545 | |
| I0331 14:37:31.634202 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.82451 (* 1 = 2.82451 loss) | |
| I0331 14:37:31.634215 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.781171 (* 1 = 0.781171 loss) | |
| I0331 14:37:31.634227 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:37:31.634238 30833 solver.cpp:245] Train net output #16: total_confidence = 0.051551 | |
| I0331 14:37:31.634250 30833 sgd_solver.cpp:106] Iteration 8000, lr = 0.05 | |
| I0331 14:39:40.006124 30833 solver.cpp:229] Iteration 8500, loss = 4.78383 | |
| I0331 14:39:40.006230 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.181818 | |
| I0331 14:39:40.006256 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.789773 | |
| I0331 14:39:40.006269 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.409091 | |
| I0331 14:39:40.006285 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.0144 (* 0.3 = 0.904321 loss) | |
| I0331 14:39:40.006299 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.82509 (* 0.3 = 0.247527 loss) | |
| I0331 14:39:40.006320 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.159091 | |
| I0331 14:39:40.006332 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.789773 | |
| I0331 14:39:40.006345 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.363636 | |
| I0331 14:39:40.006358 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.97404 (* 0.3 = 0.892211 loss) | |
| I0331 14:39:40.006371 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.778747 (* 0.3 = 0.233624 loss) | |
| I0331 14:39:40.006383 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.318182 | |
| I0331 14:39:40.006395 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.829545 | |
| I0331 14:39:40.006407 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.545455 | |
| I0331 14:39:40.006422 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.66394 (* 1 = 2.66394 loss) | |
| I0331 14:39:40.006434 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.713224 (* 1 = 0.713224 loss) | |
| I0331 14:39:40.006446 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:39:40.006458 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0110679 | |
| I0331 14:39:40.006470 30833 sgd_solver.cpp:106] Iteration 8500, lr = 0.05 | |
| I0331 14:41:48.337544 30833 solver.cpp:229] Iteration 9000, loss = 4.73846 | |
| I0331 14:41:48.337683 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.145833 | |
| I0331 14:41:48.337703 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.755682 | |
| I0331 14:41:48.337716 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.291667 | |
| I0331 14:41:48.337733 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.17189 (* 0.3 = 0.951566 loss) | |
| I0331 14:41:48.337748 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.916176 (* 0.3 = 0.274853 loss) | |
| I0331 14:41:48.337759 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.208333 | |
| I0331 14:41:48.337772 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.778409 | |
| I0331 14:41:48.337785 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.416667 | |
| I0331 14:41:48.337797 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.95901 (* 0.3 = 0.887702 loss) | |
| I0331 14:41:48.337811 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.849282 (* 0.3 = 0.254784 loss) | |
| I0331 14:41:48.337824 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.333333 | |
| I0331 14:41:48.337836 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.806818 | |
| I0331 14:41:48.337847 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.5 | |
| I0331 14:41:48.337862 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.5645 (* 1 = 2.5645 loss) | |
| I0331 14:41:48.337875 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.738579 (* 1 = 0.738579 loss) | |
| I0331 14:41:48.337888 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:41:48.337899 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0133058 | |
| I0331 14:41:48.337913 30833 sgd_solver.cpp:106] Iteration 9000, lr = 0.05 | |
| I0331 14:43:56.680702 30833 solver.cpp:229] Iteration 9500, loss = 4.69158 | |
| I0331 14:43:56.680842 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.23913 | |
| I0331 14:43:56.680862 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.767045 | |
| I0331 14:43:56.680876 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.347826 | |
| I0331 14:43:56.680894 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.06792 (* 0.3 = 0.920375 loss) | |
| I0331 14:43:56.680915 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.941894 (* 0.3 = 0.282568 loss) | |
| I0331 14:43:56.680935 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.173913 | |
| I0331 14:43:56.680948 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.744318 | |
| I0331 14:43:56.680960 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.369565 | |
| I0331 14:43:56.680974 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.03944 (* 0.3 = 0.911831 loss) | |
| I0331 14:43:56.680987 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.975006 (* 0.3 = 0.292502 loss) | |
| I0331 14:43:56.680999 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.369565 | |
| I0331 14:43:56.681011 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.801136 | |
| I0331 14:43:56.681023 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.543478 | |
| I0331 14:43:56.681037 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.53121 (* 1 = 2.53121 loss) | |
| I0331 14:43:56.681051 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.781847 (* 1 = 0.781847 loss) | |
| I0331 14:43:56.681062 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:43:56.681074 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0170888 | |
| I0331 14:43:56.681089 30833 sgd_solver.cpp:106] Iteration 9500, lr = 0.05 | |
| I0331 14:46:04.899308 30833 solver.cpp:338] Iteration 10000, Testing net (#0) | |
| I0331 14:46:34.655771 30833 solver.cpp:393] Test loss: 4.54261 | |
| I0331 14:46:34.655815 30833 solver.cpp:406] Test net output #0: loss1/accuracy = 0.226432 | |
| I0331 14:46:34.655832 30833 solver.cpp:406] Test net output #1: loss1/accuracy_incl_empty = 0.798273 | |
| I0331 14:46:34.655843 30833 solver.cpp:406] Test net output #2: loss1/accuracy_top3 = 0.474629 | |
| I0331 14:46:34.655859 30833 solver.cpp:406] Test net output #3: loss1/cross_entropy_loss = 2.67742 (* 0.3 = 0.803227 loss) | |
| I0331 14:46:34.655874 30833 solver.cpp:406] Test net output #4: loss1/cross_entropy_loss_incl_empty = 0.724737 (* 0.3 = 0.217421 loss) | |
| I0331 14:46:34.655885 30833 solver.cpp:406] Test net output #5: loss2/accuracy = 0.306462 | |
| I0331 14:46:34.655897 30833 solver.cpp:406] Test net output #6: loss2/accuracy_incl_empty = 0.818137 | |
| I0331 14:46:34.655908 30833 solver.cpp:406] Test net output #7: loss2/accuracy_top3 = 0.592001 | |
| I0331 14:46:34.655922 30833 solver.cpp:406] Test net output #8: loss2/cross_entropy_loss = 2.40093 (* 0.3 = 0.720279 loss) | |
| I0331 14:46:34.655936 30833 solver.cpp:406] Test net output #9: loss2/cross_entropy_loss_incl_empty = 0.646232 (* 0.3 = 0.19387 loss) | |
| I0331 14:46:34.655947 30833 solver.cpp:406] Test net output #10: loss3/accuracy = 0.427507 | |
| I0331 14:46:34.655958 30833 solver.cpp:406] Test net output #11: loss3/accuracy_incl_empty = 0.846456 | |
| I0331 14:46:34.655978 30833 solver.cpp:406] Test net output #12: loss3/accuracy_top3 = 0.690929 | |
| I0331 14:46:34.655992 30833 solver.cpp:406] Test net output #13: loss3/cross_entropy_loss = 2.04594 (* 1 = 2.04594 loss) | |
| I0331 14:46:34.656007 30833 solver.cpp:406] Test net output #14: loss3/cross_entropy_loss_incl_empty = 0.561876 (* 1 = 0.561876 loss) | |
| I0331 14:46:34.656019 30833 solver.cpp:406] Test net output #15: total_accuracy = 0.029 | |
| I0331 14:46:34.656038 30833 solver.cpp:406] Test net output #16: total_confidence = 0.0449764 | |
| I0331 14:46:34.807433 30833 solver.cpp:229] Iteration 10000, loss = 4.66354 | |
| I0331 14:46:34.807495 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.222222 | |
| I0331 14:46:34.807512 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.795455 | |
| I0331 14:46:34.807525 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.422222 | |
| I0331 14:46:34.807544 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.56397 (* 0.3 = 0.76919 loss) | |
| I0331 14:46:34.807574 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.718749 (* 0.3 = 0.215625 loss) | |
| I0331 14:46:34.807591 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.222222 | |
| I0331 14:46:34.807605 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.778409 | |
| I0331 14:46:34.807616 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.555556 | |
| I0331 14:46:34.807629 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.37118 (* 0.3 = 0.711355 loss) | |
| I0331 14:46:34.807643 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.709948 (* 0.3 = 0.212984 loss) | |
| I0331 14:46:34.807659 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.533333 | |
| I0331 14:46:34.807672 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.869318 | |
| I0331 14:46:34.807683 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.755556 | |
| I0331 14:46:34.807698 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.67265 (* 1 = 1.67265 loss) | |
| I0331 14:46:34.807711 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.477699 (* 1 = 0.477699 loss) | |
| I0331 14:46:34.807723 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.125 | |
| I0331 14:46:34.807735 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0946325 | |
| I0331 14:46:34.807747 30833 sgd_solver.cpp:106] Iteration 10000, lr = 0.05 | |
| I0331 14:48:43.155448 30833 solver.cpp:229] Iteration 10500, loss = 4.58027 | |
| I0331 14:48:43.155621 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.121951 | |
| I0331 14:48:43.155658 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.778409 | |
| I0331 14:48:43.155683 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.365854 | |
| I0331 14:48:43.155702 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.95077 (* 0.3 = 0.885231 loss) | |
| I0331 14:48:43.155717 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.788321 (* 0.3 = 0.236496 loss) | |
| I0331 14:48:43.155730 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.243902 | |
| I0331 14:48:43.155741 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.8125 | |
| I0331 14:48:43.155753 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.560976 | |
| I0331 14:48:43.155767 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.64947 (* 0.3 = 0.794841 loss) | |
| I0331 14:48:43.155781 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.681089 (* 0.3 = 0.204327 loss) | |
| I0331 14:48:43.155792 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.536585 | |
| I0331 14:48:43.155804 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.886364 | |
| I0331 14:48:43.155817 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.780488 | |
| I0331 14:48:43.155830 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.64954 (* 1 = 1.64954 loss) | |
| I0331 14:48:43.155843 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.419525 (* 1 = 0.419525 loss) | |
| I0331 14:48:43.155855 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:48:43.155866 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0140806 | |
| I0331 14:48:43.155879 30833 sgd_solver.cpp:106] Iteration 10500, lr = 0.05 | |
| I0331 14:50:51.462749 30833 solver.cpp:229] Iteration 11000, loss = 4.55398 | |
| I0331 14:50:51.462915 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.166667 | |
| I0331 14:50:51.462944 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.732955 | |
| I0331 14:50:51.462955 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.37037 | |
| I0331 14:50:51.462971 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.98994 (* 0.3 = 0.896984 loss) | |
| I0331 14:50:51.462986 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.985061 (* 0.3 = 0.295518 loss) | |
| I0331 14:50:51.462998 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.296296 | |
| I0331 14:50:51.463011 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.778409 | |
| I0331 14:50:51.463022 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.537037 | |
| I0331 14:50:51.463037 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.86914 (* 0.3 = 0.860743 loss) | |
| I0331 14:50:51.463049 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.938499 (* 0.3 = 0.28155 loss) | |
| I0331 14:50:51.463063 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.333333 | |
| I0331 14:50:51.463073 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.784091 | |
| I0331 14:50:51.463099 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.555556 | |
| I0331 14:50:51.463116 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.57946 (* 1 = 2.57946 loss) | |
| I0331 14:50:51.463130 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.84873 (* 1 = 0.84873 loss) | |
| I0331 14:50:51.463141 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:50:51.463153 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0293562 | |
| I0331 14:50:51.463166 30833 sgd_solver.cpp:106] Iteration 11000, lr = 0.05 | |
| I0331 14:52:59.742735 30833 solver.cpp:229] Iteration 11500, loss = 4.52761 | |
| I0331 14:52:59.742846 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.204082 | |
| I0331 14:52:59.742864 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.767045 | |
| I0331 14:52:59.742877 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.530612 | |
| I0331 14:52:59.742893 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.51624 (* 0.3 = 0.754872 loss) | |
| I0331 14:52:59.742908 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.778426 (* 0.3 = 0.233528 loss) | |
| I0331 14:52:59.742920 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.306122 | |
| I0331 14:52:59.742933 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.784091 | |
| I0331 14:52:59.742944 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.510204 | |
| I0331 14:52:59.742959 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.52178 (* 0.3 = 0.756535 loss) | |
| I0331 14:52:59.742971 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.817511 (* 0.3 = 0.245253 loss) | |
| I0331 14:52:59.742985 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.44898 | |
| I0331 14:52:59.742995 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.823864 | |
| I0331 14:52:59.743007 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.653061 | |
| I0331 14:52:59.743021 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.25121 (* 1 = 2.25121 loss) | |
| I0331 14:52:59.743034 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.693052 (* 1 = 0.693052 loss) | |
| I0331 14:52:59.743046 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:52:59.743057 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0134283 | |
| I0331 14:52:59.743069 30833 sgd_solver.cpp:106] Iteration 11500, lr = 0.05 | |
| I0331 14:55:08.255499 30833 solver.cpp:229] Iteration 12000, loss = 4.5202 | |
| I0331 14:55:08.255651 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.148936 | |
| I0331 14:55:08.255672 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.767045 | |
| I0331 14:55:08.255693 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.340426 | |
| I0331 14:55:08.255709 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.01304 (* 0.3 = 0.903911 loss) | |
| I0331 14:55:08.255724 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.872657 (* 0.3 = 0.261797 loss) | |
| I0331 14:55:08.255736 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.170213 | |
| I0331 14:55:08.255749 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.761364 | |
| I0331 14:55:08.255761 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.276596 | |
| I0331 14:55:08.255775 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.01407 (* 0.3 = 0.90422 loss) | |
| I0331 14:55:08.255789 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.906295 (* 0.3 = 0.271888 loss) | |
| I0331 14:55:08.255801 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.255319 | |
| I0331 14:55:08.255813 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.795455 | |
| I0331 14:55:08.255825 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.553191 | |
| I0331 14:55:08.255838 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.31274 (* 1 = 2.31274 loss) | |
| I0331 14:55:08.255852 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.677382 (* 1 = 0.677382 loss) | |
| I0331 14:55:08.255863 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:55:08.255875 30833 solver.cpp:245] Train net output #16: total_confidence = 0.00738938 | |
| I0331 14:55:08.255887 30833 sgd_solver.cpp:106] Iteration 12000, lr = 0.05 | |
| I0331 14:57:17.183115 30833 solver.cpp:229] Iteration 12500, loss = 4.43867 | |
| I0331 14:57:17.183204 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.122449 | |
| I0331 14:57:17.183223 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.75 | |
| I0331 14:57:17.183236 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.265306 | |
| I0331 14:57:17.183251 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.37841 (* 0.3 = 1.01352 loss) | |
| I0331 14:57:17.183266 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.980252 (* 0.3 = 0.294076 loss) | |
| I0331 14:57:17.183279 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.142857 | |
| I0331 14:57:17.183290 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.761364 | |
| I0331 14:57:17.183302 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.367347 | |
| I0331 14:57:17.183323 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 3.75468 (* 0.3 = 1.1264 loss) | |
| I0331 14:57:17.183337 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 1.06723 (* 0.3 = 0.32017 loss) | |
| I0331 14:57:17.183349 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.244898 | |
| I0331 14:57:17.183362 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.789773 | |
| I0331 14:57:17.183378 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.510204 | |
| I0331 14:57:17.183393 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.72232 (* 1 = 2.72232 loss) | |
| I0331 14:57:17.183405 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.771782 (* 1 = 0.771782 loss) | |
| I0331 14:57:17.183418 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:57:17.183429 30833 solver.cpp:245] Train net output #16: total_confidence = 0.00419322 | |
| I0331 14:57:17.183440 30833 sgd_solver.cpp:106] Iteration 12500, lr = 0.05 | |
| I0331 14:59:25.469430 30833 solver.cpp:229] Iteration 13000, loss = 4.47065 | |
| I0331 14:59:25.469585 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.234043 | |
| I0331 14:59:25.469605 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.789773 | |
| I0331 14:59:25.469625 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.531915 | |
| I0331 14:59:25.469641 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.41824 (* 0.3 = 0.725472 loss) | |
| I0331 14:59:25.469656 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.678096 (* 0.3 = 0.203429 loss) | |
| I0331 14:59:25.469668 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.361702 | |
| I0331 14:59:25.469681 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.829545 | |
| I0331 14:59:25.469692 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.595745 | |
| I0331 14:59:25.469707 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.22173 (* 0.3 = 0.66652 loss) | |
| I0331 14:59:25.469720 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.616299 (* 0.3 = 0.18489 loss) | |
| I0331 14:59:25.469732 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.489362 | |
| I0331 14:59:25.469744 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.852273 | |
| I0331 14:59:25.469756 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.744681 | |
| I0331 14:59:25.469770 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.57518 (* 1 = 1.57518 loss) | |
| I0331 14:59:25.469784 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.45788 (* 1 = 0.45788 loss) | |
| I0331 14:59:25.469801 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 14:59:25.469820 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0341073 | |
| I0331 14:59:25.469833 30833 sgd_solver.cpp:106] Iteration 13000, lr = 0.05 | |
| I0331 15:01:33.854226 30833 solver.cpp:229] Iteration 13500, loss = 4.44677 | |
| I0331 15:01:33.854470 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.181818 | |
| I0331 15:01:33.854491 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.784091 | |
| I0331 15:01:33.854504 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.393939 | |
| I0331 15:01:33.854519 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.79991 (* 0.3 = 0.839972 loss) | |
| I0331 15:01:33.854534 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.893624 (* 0.3 = 0.268087 loss) | |
| I0331 15:01:33.854547 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.333333 | |
| I0331 15:01:33.854558 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.818182 | |
| I0331 15:01:33.854570 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.545455 | |
| I0331 15:01:33.854583 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.454 (* 0.3 = 0.7362 loss) | |
| I0331 15:01:33.854598 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.804078 (* 0.3 = 0.241223 loss) | |
| I0331 15:01:33.854609 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.424242 | |
| I0331 15:01:33.854624 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.818182 | |
| I0331 15:01:33.854636 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.727273 | |
| I0331 15:01:33.854650 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.10602 (* 1 = 2.10602 loss) | |
| I0331 15:01:33.854663 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.772567 (* 1 = 0.772567 loss) | |
| I0331 15:01:33.854676 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 15:01:33.854687 30833 solver.cpp:245] Train net output #16: total_confidence = 0.00325553 | |
| I0331 15:01:33.854699 30833 sgd_solver.cpp:106] Iteration 13500, lr = 0.05 | |
| I0331 15:03:42.164531 30833 solver.cpp:229] Iteration 14000, loss = 4.35588 | |
| I0331 15:03:42.164687 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.395349 | |
| I0331 15:03:42.164716 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.840909 | |
| I0331 15:03:42.164729 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.651163 | |
| I0331 15:03:42.164746 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.3021 (* 0.3 = 0.69063 loss) | |
| I0331 15:03:42.164760 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.630476 (* 0.3 = 0.189143 loss) | |
| I0331 15:03:42.164772 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.418605 | |
| I0331 15:03:42.164784 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.835227 | |
| I0331 15:03:42.164796 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.744186 | |
| I0331 15:03:42.164809 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.1175 (* 0.3 = 0.635251 loss) | |
| I0331 15:03:42.164824 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.58361 (* 0.3 = 0.175083 loss) | |
| I0331 15:03:42.164836 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.581395 | |
| I0331 15:03:42.164847 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.880682 | |
| I0331 15:03:42.164860 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.860465 | |
| I0331 15:03:42.164873 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.42751 (* 1 = 1.42751 loss) | |
| I0331 15:03:42.164886 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.398335 (* 1 = 0.398335 loss) | |
| I0331 15:03:42.164898 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.125 | |
| I0331 15:03:42.164911 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0269497 | |
| I0331 15:03:42.164922 30833 sgd_solver.cpp:106] Iteration 14000, lr = 0.05 | |
| I0331 15:05:50.501094 30833 solver.cpp:229] Iteration 14500, loss = 4.36541 | |
| I0331 15:05:50.501224 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.157895 | |
| I0331 15:05:50.501243 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.715909 | |
| I0331 15:05:50.501256 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.245614 | |
| I0331 15:05:50.501271 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.02043 (* 0.3 = 0.906128 loss) | |
| I0331 15:05:50.501286 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 1.02007 (* 0.3 = 0.306022 loss) | |
| I0331 15:05:50.501298 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.22807 | |
| I0331 15:05:50.501312 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.744318 | |
| I0331 15:05:50.501322 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.508772 | |
| I0331 15:05:50.501337 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.68033 (* 0.3 = 0.804098 loss) | |
| I0331 15:05:50.501349 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.908021 (* 0.3 = 0.272406 loss) | |
| I0331 15:05:50.501361 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.385965 | |
| I0331 15:05:50.501374 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.784091 | |
| I0331 15:05:50.501385 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.614035 | |
| I0331 15:05:50.501399 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.13107 (* 1 = 2.13107 loss) | |
| I0331 15:05:50.501412 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.723368 (* 1 = 0.723368 loss) | |
| I0331 15:05:50.501425 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.125 | |
| I0331 15:05:50.501436 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0863376 | |
| I0331 15:05:50.501447 30833 sgd_solver.cpp:106] Iteration 14500, lr = 0.05 | |
| I0331 15:07:58.918556 30833 solver.cpp:338] Iteration 15000, Testing net (#0) | |
| I0331 15:08:28.648844 30833 solver.cpp:393] Test loss: 3.76422 | |
| I0331 15:08:28.648895 30833 solver.cpp:406] Test net output #0: loss1/accuracy = 0.277931 | |
| I0331 15:08:28.648911 30833 solver.cpp:406] Test net output #1: loss1/accuracy_incl_empty = 0.809273 | |
| I0331 15:08:28.648923 30833 solver.cpp:406] Test net output #2: loss1/accuracy_top3 = 0.567616 | |
| I0331 15:08:28.648938 30833 solver.cpp:406] Test net output #3: loss1/cross_entropy_loss = 2.36707 (* 0.3 = 0.71012 loss) | |
| I0331 15:08:28.648953 30833 solver.cpp:406] Test net output #4: loss1/cross_entropy_loss_incl_empty = 0.645704 (* 0.3 = 0.193711 loss) | |
| I0331 15:08:28.648964 30833 solver.cpp:406] Test net output #5: loss2/accuracy = 0.399977 | |
| I0331 15:08:28.648977 30833 solver.cpp:406] Test net output #6: loss2/accuracy_incl_empty = 0.847866 | |
| I0331 15:08:28.648988 30833 solver.cpp:406] Test net output #7: loss2/accuracy_top3 = 0.712306 | |
| I0331 15:08:28.649001 30833 solver.cpp:406] Test net output #8: loss2/cross_entropy_loss = 1.99301 (* 0.3 = 0.597902 loss) | |
| I0331 15:08:28.649014 30833 solver.cpp:406] Test net output #9: loss2/cross_entropy_loss_incl_empty = 0.518553 (* 0.3 = 0.155566 loss) | |
| I0331 15:08:28.649026 30833 solver.cpp:406] Test net output #10: loss3/accuracy = 0.556537 | |
| I0331 15:08:28.649039 30833 solver.cpp:406] Test net output #11: loss3/accuracy_incl_empty = 0.882048 | |
| I0331 15:08:28.649049 30833 solver.cpp:406] Test net output #12: loss3/accuracy_top3 = 0.784059 | |
| I0331 15:08:28.649062 30833 solver.cpp:406] Test net output #13: loss3/cross_entropy_loss = 1.66449 (* 1 = 1.66449 loss) | |
| I0331 15:08:28.649075 30833 solver.cpp:406] Test net output #14: loss3/cross_entropy_loss_incl_empty = 0.442433 (* 1 = 0.442433 loss) | |
| I0331 15:08:28.649090 30833 solver.cpp:406] Test net output #15: total_accuracy = 0.084 | |
| I0331 15:08:28.649102 30833 solver.cpp:406] Test net output #16: total_confidence = 0.119041 | |
| I0331 15:08:28.800690 30833 solver.cpp:229] Iteration 15000, loss = 4.32311 | |
| I0331 15:08:28.800748 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.380952 | |
| I0331 15:08:28.800766 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.806818 | |
| I0331 15:08:28.800779 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.595238 | |
| I0331 15:08:28.800796 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.3548 (* 0.3 = 0.706439 loss) | |
| I0331 15:08:28.800811 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.721912 (* 0.3 = 0.216574 loss) | |
| I0331 15:08:28.800822 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.380952 | |
| I0331 15:08:28.800838 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.806818 | |
| I0331 15:08:28.800850 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.690476 | |
| I0331 15:08:28.800864 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.08594 (* 0.3 = 0.625783 loss) | |
| I0331 15:08:28.800879 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.661326 (* 0.3 = 0.198398 loss) | |
| I0331 15:08:28.800891 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.619048 | |
| I0331 15:08:28.800902 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.892045 | |
| I0331 15:08:28.800915 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.857143 | |
| I0331 15:08:28.800928 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.15659 (* 1 = 1.15659 loss) | |
| I0331 15:08:28.800942 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.351903 (* 1 = 0.351903 loss) | |
| I0331 15:08:28.800954 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.125 | |
| I0331 15:08:28.800966 30833 solver.cpp:245] Train net output #16: total_confidence = 0.10664 | |
| I0331 15:08:28.800979 30833 sgd_solver.cpp:106] Iteration 15000, lr = 0.05 | |
| I0331 15:10:36.974414 30833 solver.cpp:229] Iteration 15500, loss = 4.20944 | |
| I0331 15:10:36.974553 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.311111 | |
| I0331 15:10:36.974581 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.801136 | |
| I0331 15:10:36.974613 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.511111 | |
| I0331 15:10:36.974647 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.43264 (* 0.3 = 0.729792 loss) | |
| I0331 15:10:36.974669 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.702713 (* 0.3 = 0.210814 loss) | |
| I0331 15:10:36.974683 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.466667 | |
| I0331 15:10:36.974694 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.829545 | |
| I0331 15:10:36.974706 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.6 | |
| I0331 15:10:36.974720 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.13287 (* 0.3 = 0.63986 loss) | |
| I0331 15:10:36.974733 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.649698 (* 0.3 = 0.19491 loss) | |
| I0331 15:10:36.974745 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.6 | |
| I0331 15:10:36.974757 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.880682 | |
| I0331 15:10:36.974768 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.8 | |
| I0331 15:10:36.974782 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.1831 (* 1 = 1.1831 loss) | |
| I0331 15:10:36.974795 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.362929 (* 1 = 0.362929 loss) | |
| I0331 15:10:36.974807 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.25 | |
| I0331 15:10:36.974819 30833 solver.cpp:245] Train net output #16: total_confidence = 0.092648 | |
| I0331 15:10:36.974831 30833 sgd_solver.cpp:106] Iteration 15500, lr = 0.05 | |
| I0331 15:12:45.462532 30833 solver.cpp:229] Iteration 16000, loss = 4.27627 | |
| I0331 15:12:45.462759 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.340426 | |
| I0331 15:12:45.462779 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.801136 | |
| I0331 15:12:45.462792 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.553191 | |
| I0331 15:12:45.462808 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.34865 (* 0.3 = 0.704594 loss) | |
| I0331 15:12:45.462824 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.711107 (* 0.3 = 0.213332 loss) | |
| I0331 15:12:45.462836 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.340426 | |
| I0331 15:12:45.462848 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.795455 | |
| I0331 15:12:45.462859 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.574468 | |
| I0331 15:12:45.462873 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.41239 (* 0.3 = 0.723716 loss) | |
| I0331 15:12:45.462888 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.744407 (* 0.3 = 0.223322 loss) | |
| I0331 15:12:45.462899 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.425532 | |
| I0331 15:12:45.462911 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.806818 | |
| I0331 15:12:45.462924 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.617021 | |
| I0331 15:12:45.462936 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.06563 (* 1 = 2.06563 loss) | |
| I0331 15:12:45.462950 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.661263 (* 1 = 0.661263 loss) | |
| I0331 15:12:45.462962 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.125 | |
| I0331 15:12:45.462975 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0655041 | |
| I0331 15:12:45.462986 30833 sgd_solver.cpp:106] Iteration 16000, lr = 0.05 | |
| I0331 15:14:53.690562 30833 solver.cpp:229] Iteration 16500, loss = 4.12448 | |
| I0331 15:14:53.690713 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.292683 | |
| I0331 15:14:53.690742 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.8125 | |
| I0331 15:14:53.690754 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.463415 | |
| I0331 15:14:53.690770 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.41529 (* 0.3 = 0.724587 loss) | |
| I0331 15:14:53.690785 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.678429 (* 0.3 = 0.203529 loss) | |
| I0331 15:14:53.690798 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.487805 | |
| I0331 15:14:53.690810 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.852273 | |
| I0331 15:14:53.690821 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.658537 | |
| I0331 15:14:53.690835 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 1.92108 (* 0.3 = 0.576323 loss) | |
| I0331 15:14:53.690848 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.569106 (* 0.3 = 0.170732 loss) | |
| I0331 15:14:53.690860 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.536585 | |
| I0331 15:14:53.690872 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.857955 | |
| I0331 15:14:53.690884 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.780488 | |
| I0331 15:14:53.690897 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.23563 (* 1 = 1.23563 loss) | |
| I0331 15:14:53.690912 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.372331 (* 1 = 0.372331 loss) | |
| I0331 15:14:53.690923 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.125 | |
| I0331 15:14:53.690935 30833 solver.cpp:245] Train net output #16: total_confidence = 0.151016 | |
| I0331 15:14:53.690946 30833 sgd_solver.cpp:106] Iteration 16500, lr = 0.05 | |
| I0331 15:17:01.982213 30833 solver.cpp:229] Iteration 17000, loss = 4.17168 | |
| I0331 15:17:01.982323 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.192308 | |
| I0331 15:17:01.982343 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.761364 | |
| I0331 15:17:01.982357 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.307692 | |
| I0331 15:17:01.982372 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.19046 (* 0.3 = 0.957138 loss) | |
| I0331 15:17:01.982386 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.963534 (* 0.3 = 0.28906 loss) | |
| I0331 15:17:01.982398 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.211538 | |
| I0331 15:17:01.982410 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.767045 | |
| I0331 15:17:01.982422 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.365385 | |
| I0331 15:17:01.982436 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.91056 (* 0.3 = 0.873167 loss) | |
| I0331 15:17:01.982450 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.88238 (* 0.3 = 0.264714 loss) | |
| I0331 15:17:01.982461 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.480769 | |
| I0331 15:17:01.982475 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.846591 | |
| I0331 15:17:01.982487 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.596154 | |
| I0331 15:17:01.982512 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.02312 (* 1 = 2.02312 loss) | |
| I0331 15:17:01.982542 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.609883 (* 1 = 0.609883 loss) | |
| I0331 15:17:01.982554 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 15:17:01.982566 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0221853 | |
| I0331 15:17:01.982578 30833 sgd_solver.cpp:106] Iteration 17000, lr = 0.05 | |
| I0331 15:19:10.419070 30833 solver.cpp:229] Iteration 17500, loss = 4.14048 | |
| I0331 15:19:10.419220 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.0952381 | |
| I0331 15:19:10.419240 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.744318 | |
| I0331 15:19:10.419261 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.380952 | |
| I0331 15:19:10.419277 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.80184 (* 0.3 = 0.840551 loss) | |
| I0331 15:19:10.419292 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.820701 (* 0.3 = 0.24621 loss) | |
| I0331 15:19:10.419304 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.309524 | |
| I0331 15:19:10.419317 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.8125 | |
| I0331 15:19:10.419328 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.595238 | |
| I0331 15:19:10.419342 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.16946 (* 0.3 = 0.650838 loss) | |
| I0331 15:19:10.419356 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.607474 (* 0.3 = 0.182242 loss) | |
| I0331 15:19:10.419368 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.5 | |
| I0331 15:19:10.419380 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.863636 | |
| I0331 15:19:10.419391 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.761905 | |
| I0331 15:19:10.419405 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.67982 (* 1 = 1.67982 loss) | |
| I0331 15:19:10.419419 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.486492 (* 1 = 0.486492 loss) | |
| I0331 15:19:10.419430 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.125 | |
| I0331 15:19:10.419442 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0632114 | |
| I0331 15:19:10.419455 30833 sgd_solver.cpp:106] Iteration 17500, lr = 0.05 | |
| I0331 15:21:18.801589 30833 solver.cpp:229] Iteration 18000, loss = 4.13569 | |
| I0331 15:21:18.801720 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.2 | |
| I0331 15:21:18.801739 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.778409 | |
| I0331 15:21:18.801753 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.4 | |
| I0331 15:21:18.801769 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.80436 (* 0.3 = 0.841308 loss) | |
| I0331 15:21:18.801784 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.851323 (* 0.3 = 0.255397 loss) | |
| I0331 15:21:18.801796 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.177778 | |
| I0331 15:21:18.801807 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.761364 | |
| I0331 15:21:18.801820 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.377778 | |
| I0331 15:21:18.801832 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.81784 (* 0.3 = 0.845351 loss) | |
| I0331 15:21:18.801846 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.865367 (* 0.3 = 0.25961 loss) | |
| I0331 15:21:18.801858 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.377778 | |
| I0331 15:21:18.801869 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.801136 | |
| I0331 15:21:18.801882 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.577778 | |
| I0331 15:21:18.801895 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.03557 (* 1 = 2.03557 loss) | |
| I0331 15:21:18.801908 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.642305 (* 1 = 0.642305 loss) | |
| I0331 15:21:18.801920 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 15:21:18.801933 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0433667 | |
| I0331 15:21:18.801944 30833 sgd_solver.cpp:106] Iteration 18000, lr = 0.05 | |
| I0331 15:23:27.006252 30833 solver.cpp:229] Iteration 18500, loss = 4.16682 | |
| I0331 15:23:27.006431 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.25 | |
| I0331 15:23:27.006469 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.795455 | |
| I0331 15:23:27.006492 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.444444 | |
| I0331 15:23:27.006520 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.46714 (* 0.3 = 0.740143 loss) | |
| I0331 15:23:27.006538 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.71485 (* 0.3 = 0.214455 loss) | |
| I0331 15:23:27.006551 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.361111 | |
| I0331 15:23:27.006563 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.823864 | |
| I0331 15:23:27.006575 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.583333 | |
| I0331 15:23:27.006588 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.14269 (* 0.3 = 0.642806 loss) | |
| I0331 15:23:27.006603 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.67488 (* 0.3 = 0.202464 loss) | |
| I0331 15:23:27.006614 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.666667 | |
| I0331 15:23:27.006626 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.914773 | |
| I0331 15:23:27.006639 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.805556 | |
| I0331 15:23:27.006652 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.21584 (* 1 = 1.21584 loss) | |
| I0331 15:23:27.006666 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.35364 (* 1 = 0.35364 loss) | |
| I0331 15:23:27.006678 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.375 | |
| I0331 15:23:27.006690 30833 solver.cpp:245] Train net output #16: total_confidence = 0.164147 | |
| I0331 15:23:27.006702 30833 sgd_solver.cpp:106] Iteration 18500, lr = 0.05 | |
| I0331 15:25:35.457944 30833 solver.cpp:229] Iteration 19000, loss = 4.0781 | |
| I0331 15:25:35.458086 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.234043 | |
| I0331 15:25:35.458106 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.784091 | |
| I0331 15:25:35.458120 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.489362 | |
| I0331 15:25:35.458137 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.60638 (* 0.3 = 0.781915 loss) | |
| I0331 15:25:35.458151 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.756356 (* 0.3 = 0.226907 loss) | |
| I0331 15:25:35.458163 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.468085 | |
| I0331 15:25:35.458175 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.829545 | |
| I0331 15:25:35.458187 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.680851 | |
| I0331 15:25:35.458201 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.01921 (* 0.3 = 0.605763 loss) | |
| I0331 15:25:35.458215 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.616906 (* 0.3 = 0.185072 loss) | |
| I0331 15:25:35.458227 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.638298 | |
| I0331 15:25:35.458240 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.903409 | |
| I0331 15:25:35.458250 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.829787 | |
| I0331 15:25:35.458264 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.30768 (* 1 = 1.30768 loss) | |
| I0331 15:25:35.458279 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.37756 (* 1 = 0.37756 loss) | |
| I0331 15:25:35.458292 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.125 | |
| I0331 15:25:35.458312 30833 solver.cpp:245] Train net output #16: total_confidence = 0.141337 | |
| I0331 15:25:35.458324 30833 sgd_solver.cpp:106] Iteration 19000, lr = 0.05 | |
| I0331 15:27:43.799993 30833 solver.cpp:229] Iteration 19500, loss = 4.05507 | |
| I0331 15:27:43.800142 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.173913 | |
| I0331 15:27:43.800161 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.761364 | |
| I0331 15:27:43.800174 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.413043 | |
| I0331 15:27:43.800199 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.93772 (* 0.3 = 0.881317 loss) | |
| I0331 15:27:43.800215 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.900039 (* 0.3 = 0.270012 loss) | |
| I0331 15:27:43.800226 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.26087 | |
| I0331 15:27:43.800240 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.778409 | |
| I0331 15:27:43.800251 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.521739 | |
| I0331 15:27:43.800266 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.65088 (* 0.3 = 0.795265 loss) | |
| I0331 15:27:43.800279 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.802977 (* 0.3 = 0.240893 loss) | |
| I0331 15:27:43.800292 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.456522 | |
| I0331 15:27:43.800302 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.857955 | |
| I0331 15:27:43.800314 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.630435 | |
| I0331 15:27:43.800328 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.24696 (* 1 = 2.24696 loss) | |
| I0331 15:27:43.800341 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.615054 (* 1 = 0.615054 loss) | |
| I0331 15:27:43.800353 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 15:27:43.800364 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0799842 | |
| I0331 15:27:43.800376 30833 sgd_solver.cpp:106] Iteration 19500, lr = 0.05 | |
| I0331 15:29:52.022130 30833 solver.cpp:338] Iteration 20000, Testing net (#0) | |
| I0331 15:30:21.782045 30833 solver.cpp:393] Test loss: 3.49304 | |
| I0331 15:30:21.782094 30833 solver.cpp:406] Test net output #0: loss1/accuracy = 0.289679 | |
| I0331 15:30:21.782109 30833 solver.cpp:406] Test net output #1: loss1/accuracy_incl_empty = 0.816955 | |
| I0331 15:30:21.782121 30833 solver.cpp:406] Test net output #2: loss1/accuracy_top3 = 0.564894 | |
| I0331 15:30:21.782136 30833 solver.cpp:406] Test net output #3: loss1/cross_entropy_loss = 2.54961 (* 0.3 = 0.764882 loss) | |
| I0331 15:30:21.782150 30833 solver.cpp:406] Test net output #4: loss1/cross_entropy_loss_incl_empty = 0.675547 (* 0.3 = 0.202664 loss) | |
| I0331 15:30:21.782162 30833 solver.cpp:406] Test net output #5: loss2/accuracy = 0.459066 | |
| I0331 15:30:21.782174 30833 solver.cpp:406] Test net output #6: loss2/accuracy_incl_empty = 0.830547 | |
| I0331 15:30:21.782186 30833 solver.cpp:406] Test net output #7: loss2/accuracy_top3 = 0.738938 | |
| I0331 15:30:21.782198 30833 solver.cpp:406] Test net output #8: loss2/cross_entropy_loss = 1.85701 (* 0.3 = 0.557104 loss) | |
| I0331 15:30:21.782212 30833 solver.cpp:406] Test net output #9: loss2/cross_entropy_loss_incl_empty = 0.586171 (* 0.3 = 0.175851 loss) | |
| I0331 15:30:21.782224 30833 solver.cpp:406] Test net output #10: loss3/accuracy = 0.62627 | |
| I0331 15:30:21.782235 30833 solver.cpp:406] Test net output #11: loss3/accuracy_incl_empty = 0.880593 | |
| I0331 15:30:21.782246 30833 solver.cpp:406] Test net output #12: loss3/accuracy_top3 = 0.823604 | |
| I0331 15:30:21.782259 30833 solver.cpp:406] Test net output #13: loss3/cross_entropy_loss = 1.35968 (* 1 = 1.35968 loss) | |
| I0331 15:30:21.782272 30833 solver.cpp:406] Test net output #14: loss3/cross_entropy_loss_incl_empty = 0.432853 (* 1 = 0.432853 loss) | |
| I0331 15:30:21.782284 30833 solver.cpp:406] Test net output #15: total_accuracy = 0.097 | |
| I0331 15:30:21.782295 30833 solver.cpp:406] Test net output #16: total_confidence = 0.114111 | |
| I0331 15:30:21.933578 30833 solver.cpp:229] Iteration 20000, loss = 4.01855 | |
| I0331 15:30:21.933624 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.297872 | |
| I0331 15:30:21.933640 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.795455 | |
| I0331 15:30:21.933652 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.531915 | |
| I0331 15:30:21.933668 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.41103 (* 0.3 = 0.723309 loss) | |
| I0331 15:30:21.933682 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.716025 (* 0.3 = 0.214808 loss) | |
| I0331 15:30:21.933694 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.361702 | |
| I0331 15:30:21.933706 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.818182 | |
| I0331 15:30:21.933718 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.744681 | |
| I0331 15:30:21.933732 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 1.88836 (* 0.3 = 0.566507 loss) | |
| I0331 15:30:21.933745 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.574079 (* 0.3 = 0.172224 loss) | |
| I0331 15:30:21.933758 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.744681 | |
| I0331 15:30:21.933769 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.920455 | |
| I0331 15:30:21.933787 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.829787 | |
| I0331 15:30:21.933804 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 0.987179 (* 1 = 0.987179 loss) | |
| I0331 15:30:21.933817 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.303212 (* 1 = 0.303212 loss) | |
| I0331 15:30:21.933830 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.25 | |
| I0331 15:30:21.933840 30833 solver.cpp:245] Train net output #16: total_confidence = 0.152004 | |
| I0331 15:30:21.933852 30833 sgd_solver.cpp:106] Iteration 20000, lr = 0.05 | |
| I0331 15:32:30.181273 30833 solver.cpp:229] Iteration 20500, loss = 4.02224 | |
| I0331 15:32:30.181403 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.285714 | |
| I0331 15:32:30.181422 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.784091 | |
| I0331 15:32:30.181435 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.489796 | |
| I0331 15:32:30.181459 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.92992 (* 0.3 = 0.878977 loss) | |
| I0331 15:32:30.181474 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.878913 (* 0.3 = 0.263674 loss) | |
| I0331 15:32:30.181486 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.285714 | |
| I0331 15:32:30.181499 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.789773 | |
| I0331 15:32:30.181510 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.44898 | |
| I0331 15:32:30.181524 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.72747 (* 0.3 = 0.818242 loss) | |
| I0331 15:32:30.181537 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.802128 (* 0.3 = 0.240638 loss) | |
| I0331 15:32:30.181550 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.55102 | |
| I0331 15:32:30.181561 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.852273 | |
| I0331 15:32:30.181572 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.77551 | |
| I0331 15:32:30.181586 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.65601 (* 1 = 1.65601 loss) | |
| I0331 15:32:30.181599 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.540818 (* 1 = 0.540818 loss) | |
| I0331 15:32:30.181612 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 15:32:30.181622 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0152233 | |
| I0331 15:32:30.181634 30833 sgd_solver.cpp:106] Iteration 20500, lr = 0.05 | |
| I0331 15:34:38.474385 30833 solver.cpp:229] Iteration 21000, loss = 3.98619 | |
| I0331 15:34:38.474541 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.340909 | |
| I0331 15:34:38.474562 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.806818 | |
| I0331 15:34:38.474575 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.522727 | |
| I0331 15:34:38.474594 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.5301 (* 0.3 = 0.759029 loss) | |
| I0331 15:34:38.474609 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.792053 (* 0.3 = 0.237616 loss) | |
| I0331 15:34:38.474624 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.295455 | |
| I0331 15:34:38.474640 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.795455 | |
| I0331 15:34:38.474653 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.522727 | |
| I0331 15:34:38.474668 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.24762 (* 0.3 = 0.674287 loss) | |
| I0331 15:34:38.474680 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.681556 (* 0.3 = 0.204467 loss) | |
| I0331 15:34:38.474694 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.454545 | |
| I0331 15:34:38.474705 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.846591 | |
| I0331 15:34:38.474717 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.75 | |
| I0331 15:34:38.474731 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.64547 (* 1 = 1.64547 loss) | |
| I0331 15:34:38.474745 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.502386 (* 1 = 0.502386 loss) | |
| I0331 15:34:38.474757 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.25 | |
| I0331 15:34:38.474769 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0798219 | |
| I0331 15:34:38.474781 30833 sgd_solver.cpp:106] Iteration 21000, lr = 0.05 | |
| I0331 15:36:46.973562 30833 solver.cpp:229] Iteration 21500, loss = 3.9237 | |
| I0331 15:36:46.973675 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.255319 | |
| I0331 15:36:46.973695 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.801136 | |
| I0331 15:36:46.973707 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.425532 | |
| I0331 15:36:46.973723 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 3.01765 (* 0.3 = 0.905296 loss) | |
| I0331 15:36:46.973737 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.838396 (* 0.3 = 0.251519 loss) | |
| I0331 15:36:46.973750 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.191489 | |
| I0331 15:36:46.973762 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.784091 | |
| I0331 15:36:46.973774 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.489362 | |
| I0331 15:36:46.973788 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.80188 (* 0.3 = 0.840563 loss) | |
| I0331 15:36:46.973801 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.768203 (* 0.3 = 0.230461 loss) | |
| I0331 15:36:46.973814 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.510638 | |
| I0331 15:36:46.973824 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.869318 | |
| I0331 15:36:46.973836 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.808511 | |
| I0331 15:36:46.973850 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.50091 (* 1 = 1.50091 loss) | |
| I0331 15:36:46.973863 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.416986 (* 1 = 0.416986 loss) | |
| I0331 15:36:46.973875 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 15:36:46.973886 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0331543 | |
| I0331 15:36:46.973897 30833 sgd_solver.cpp:106] Iteration 21500, lr = 0.05 | |
| I0331 15:38:55.750946 30833 solver.cpp:229] Iteration 22000, loss = 4.01777 | |
| I0331 15:38:55.751087 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.302326 | |
| I0331 15:38:55.751107 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.818182 | |
| I0331 15:38:55.751127 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.581395 | |
| I0331 15:38:55.751142 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.28421 (* 0.3 = 0.685262 loss) | |
| I0331 15:38:55.751157 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.623868 (* 0.3 = 0.18716 loss) | |
| I0331 15:38:55.751169 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.395349 | |
| I0331 15:38:55.751183 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.806818 | |
| I0331 15:38:55.751194 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.744186 | |
| I0331 15:38:55.751219 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 1.79213 (* 0.3 = 0.53764 loss) | |
| I0331 15:38:55.751235 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.570915 (* 0.3 = 0.171275 loss) | |
| I0331 15:38:55.751247 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.55814 | |
| I0331 15:38:55.751260 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.857955 | |
| I0331 15:38:55.751271 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.813953 | |
| I0331 15:38:55.751284 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.20954 (* 1 = 1.20954 loss) | |
| I0331 15:38:55.751298 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.379969 (* 1 = 0.379969 loss) | |
| I0331 15:38:55.751310 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 15:38:55.751322 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0554934 | |
| I0331 15:38:55.751333 30833 sgd_solver.cpp:106] Iteration 22000, lr = 0.05 | |
| I0331 15:41:04.162755 30833 solver.cpp:229] Iteration 22500, loss = 3.84244 | |
| I0331 15:41:04.162883 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.159091 | |
| I0331 15:41:04.162902 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.767045 | |
| I0331 15:41:04.162915 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.454545 | |
| I0331 15:41:04.162930 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.80886 (* 0.3 = 0.842659 loss) | |
| I0331 15:41:04.162945 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.852786 (* 0.3 = 0.255836 loss) | |
| I0331 15:41:04.162957 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.295455 | |
| I0331 15:41:04.162969 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.784091 | |
| I0331 15:41:04.162981 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.522727 | |
| I0331 15:41:04.162995 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.34702 (* 0.3 = 0.704106 loss) | |
| I0331 15:41:04.163009 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.767773 (* 0.3 = 0.230332 loss) | |
| I0331 15:41:04.163020 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.613636 | |
| I0331 15:41:04.163033 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.880682 | |
| I0331 15:41:04.163043 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.795455 | |
| I0331 15:41:04.163064 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.47666 (* 1 = 1.47666 loss) | |
| I0331 15:41:04.163079 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.526908 (* 1 = 0.526908 loss) | |
| I0331 15:41:04.163105 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.25 | |
| I0331 15:41:04.163117 30833 solver.cpp:245] Train net output #16: total_confidence = 0.138594 | |
| I0331 15:41:04.163128 30833 sgd_solver.cpp:106] Iteration 22500, lr = 0.05 | |
| I0331 15:43:12.462443 30833 solver.cpp:229] Iteration 23000, loss = 3.88875 | |
| I0331 15:43:12.462602 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.23913 | |
| I0331 15:43:12.462641 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.789773 | |
| I0331 15:43:12.462666 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.413043 | |
| I0331 15:43:12.462689 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.7604 (* 0.3 = 0.828121 loss) | |
| I0331 15:43:12.462704 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.791546 (* 0.3 = 0.237464 loss) | |
| I0331 15:43:12.462718 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.26087 | |
| I0331 15:43:12.462729 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.789773 | |
| I0331 15:43:12.462741 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.521739 | |
| I0331 15:43:12.462754 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.76687 (* 0.3 = 0.830062 loss) | |
| I0331 15:43:12.462769 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.815582 (* 0.3 = 0.244675 loss) | |
| I0331 15:43:12.462780 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.521739 | |
| I0331 15:43:12.462792 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.869318 | |
| I0331 15:43:12.462803 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.73913 | |
| I0331 15:43:12.462817 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.61165 (* 1 = 1.61165 loss) | |
| I0331 15:43:12.462831 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.461034 (* 1 = 0.461034 loss) | |
| I0331 15:43:12.462842 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.125 | |
| I0331 15:43:12.462855 30833 solver.cpp:245] Train net output #16: total_confidence = 0.122027 | |
| I0331 15:43:12.462867 30833 sgd_solver.cpp:106] Iteration 23000, lr = 0.05 | |
| I0331 15:45:21.383771 30833 solver.cpp:229] Iteration 23500, loss = 3.82012 | |
| I0331 15:45:21.384054 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.28 | |
| I0331 15:45:21.384075 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.772727 | |
| I0331 15:45:21.384090 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.4 | |
| I0331 15:45:21.384115 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.52856 (* 0.3 = 0.758568 loss) | |
| I0331 15:45:21.384153 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.784367 (* 0.3 = 0.23531 loss) | |
| I0331 15:45:21.384169 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.34 | |
| I0331 15:45:21.384181 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.806818 | |
| I0331 15:45:21.384193 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.46 | |
| I0331 15:45:21.384215 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.59785 (* 0.3 = 0.779355 loss) | |
| I0331 15:45:21.384228 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.765982 (* 0.3 = 0.229795 loss) | |
| I0331 15:45:21.384240 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.46 | |
| I0331 15:45:21.384253 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.829545 | |
| I0331 15:45:21.384263 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.74 | |
| I0331 15:45:21.384277 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.74627 (* 1 = 1.74627 loss) | |
| I0331 15:45:21.384290 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.573439 (* 1 = 0.573439 loss) | |
| I0331 15:45:21.384302 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 15:45:21.384315 30833 solver.cpp:245] Train net output #16: total_confidence = 0.066935 | |
| I0331 15:45:21.384325 30833 sgd_solver.cpp:106] Iteration 23500, lr = 0.05 | |
| I0331 15:47:29.720731 30833 solver.cpp:229] Iteration 24000, loss = 3.85473 | |
| I0331 15:47:29.720876 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.326531 | |
| I0331 15:47:29.720896 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.795455 | |
| I0331 15:47:29.720916 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.571429 | |
| I0331 15:47:29.720932 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.24049 (* 0.3 = 0.672147 loss) | |
| I0331 15:47:29.720952 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.691848 (* 0.3 = 0.207554 loss) | |
| I0331 15:47:29.720973 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.367347 | |
| I0331 15:47:29.720986 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.8125 | |
| I0331 15:47:29.720999 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.632653 | |
| I0331 15:47:29.721012 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 1.90126 (* 0.3 = 0.570377 loss) | |
| I0331 15:47:29.721026 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.571497 (* 0.3 = 0.171449 loss) | |
| I0331 15:47:29.721038 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.653061 | |
| I0331 15:47:29.721050 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.897727 | |
| I0331 15:47:29.721062 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.857143 | |
| I0331 15:47:29.721076 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.08437 (* 1 = 1.08437 loss) | |
| I0331 15:47:29.721093 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.321856 (* 1 = 0.321856 loss) | |
| I0331 15:47:29.721104 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.25 | |
| I0331 15:47:29.721117 30833 solver.cpp:245] Train net output #16: total_confidence = 0.155403 | |
| I0331 15:47:29.721129 30833 sgd_solver.cpp:106] Iteration 24000, lr = 0.05 | |
| I0331 15:49:38.177618 30833 solver.cpp:229] Iteration 24500, loss = 3.89224 | |
| I0331 15:49:38.177736 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.267857 | |
| I0331 15:49:38.177763 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.767045 | |
| I0331 15:49:38.177777 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.482143 | |
| I0331 15:49:38.177793 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.65027 (* 0.3 = 0.795081 loss) | |
| I0331 15:49:38.177808 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.861002 (* 0.3 = 0.258301 loss) | |
| I0331 15:49:38.177820 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.267857 | |
| I0331 15:49:38.177832 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.761364 | |
| I0331 15:49:38.177844 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.589286 | |
| I0331 15:49:38.177857 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.60245 (* 0.3 = 0.780736 loss) | |
| I0331 15:49:38.177871 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.845886 (* 0.3 = 0.253766 loss) | |
| I0331 15:49:38.177883 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.482143 | |
| I0331 15:49:38.177896 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.835227 | |
| I0331 15:49:38.177907 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.785714 | |
| I0331 15:49:38.177920 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.6155 (* 1 = 1.6155 loss) | |
| I0331 15:49:38.177934 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.538254 (* 1 = 0.538254 loss) | |
| I0331 15:49:38.177947 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 15:49:38.177958 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0526562 | |
| I0331 15:49:38.177969 30833 sgd_solver.cpp:106] Iteration 24500, lr = 0.05 | |
| I0331 15:51:46.481861 30833 solver.cpp:338] Iteration 25000, Testing net (#0) | |
| I0331 15:52:16.220532 30833 solver.cpp:393] Test loss: 3.6671 | |
| I0331 15:52:16.220577 30833 solver.cpp:406] Test net output #0: loss1/accuracy = 0.300315 | |
| I0331 15:52:16.220593 30833 solver.cpp:406] Test net output #1: loss1/accuracy_incl_empty = 0.823864 | |
| I0331 15:52:16.220605 30833 solver.cpp:406] Test net output #2: loss1/accuracy_top3 = 0.579975 | |
| I0331 15:52:16.220620 30833 solver.cpp:406] Test net output #3: loss1/cross_entropy_loss = 2.46529 (* 0.3 = 0.739587 loss) | |
| I0331 15:52:16.220635 30833 solver.cpp:406] Test net output #4: loss1/cross_entropy_loss_incl_empty = 0.635226 (* 0.3 = 0.190568 loss) | |
| I0331 15:52:16.220648 30833 solver.cpp:406] Test net output #5: loss2/accuracy = 0.470451 | |
| I0331 15:52:16.220659 30833 solver.cpp:406] Test net output #6: loss2/accuracy_incl_empty = 0.860821 | |
| I0331 15:52:16.220670 30833 solver.cpp:406] Test net output #7: loss2/accuracy_top3 = 0.732638 | |
| I0331 15:52:16.220685 30833 solver.cpp:406] Test net output #8: loss2/cross_entropy_loss = 1.87896 (* 0.3 = 0.563687 loss) | |
| I0331 15:52:16.220697 30833 solver.cpp:406] Test net output #9: loss2/cross_entropy_loss_incl_empty = 0.50128 (* 0.3 = 0.150384 loss) | |
| I0331 15:52:16.220710 30833 solver.cpp:406] Test net output #10: loss3/accuracy = 0.600488 | |
| I0331 15:52:16.220721 30833 solver.cpp:406] Test net output #11: loss3/accuracy_incl_empty = 0.899184 | |
| I0331 15:52:16.220731 30833 solver.cpp:406] Test net output #12: loss3/accuracy_top3 = 0.787468 | |
| I0331 15:52:16.220746 30833 solver.cpp:406] Test net output #13: loss3/cross_entropy_loss = 1.61045 (* 1 = 1.61045 loss) | |
| I0331 15:52:16.220758 30833 solver.cpp:406] Test net output #14: loss3/cross_entropy_loss_incl_empty = 0.412429 (* 1 = 0.412429 loss) | |
| I0331 15:52:16.220770 30833 solver.cpp:406] Test net output #15: total_accuracy = 0.187 | |
| I0331 15:52:16.220782 30833 solver.cpp:406] Test net output #16: total_confidence = 0.193059 | |
| I0331 15:52:16.371376 30833 solver.cpp:229] Iteration 25000, loss = 3.80848 | |
| I0331 15:52:16.371422 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.204082 | |
| I0331 15:52:16.371438 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.772727 | |
| I0331 15:52:16.371450 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.428571 | |
| I0331 15:52:16.371465 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.71733 (* 0.3 = 0.815198 loss) | |
| I0331 15:52:16.371479 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.797956 (* 0.3 = 0.239387 loss) | |
| I0331 15:52:16.371491 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.285714 | |
| I0331 15:52:16.371505 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.778409 | |
| I0331 15:52:16.371516 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.469388 | |
| I0331 15:52:16.371529 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.75147 (* 0.3 = 0.825442 loss) | |
| I0331 15:52:16.371543 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.839858 (* 0.3 = 0.251958 loss) | |
| I0331 15:52:16.371556 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.469388 | |
| I0331 15:52:16.371567 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.835227 | |
| I0331 15:52:16.371578 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.55102 | |
| I0331 15:52:16.371592 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.1445 (* 1 = 2.1445 loss) | |
| I0331 15:52:16.371609 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.647818 (* 1 = 0.647818 loss) | |
| I0331 15:52:16.371621 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.375 | |
| I0331 15:52:16.371634 30833 solver.cpp:245] Train net output #16: total_confidence = 0.142649 | |
| I0331 15:52:16.371645 30833 sgd_solver.cpp:106] Iteration 25000, lr = 0.05 | |
| I0331 15:54:25.434267 30833 solver.cpp:229] Iteration 25500, loss = 3.79104 | |
| I0331 15:54:25.434455 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.326087 | |
| I0331 15:54:25.434486 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.801136 | |
| I0331 15:54:25.434499 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.543478 | |
| I0331 15:54:25.434516 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.03708 (* 0.3 = 0.611124 loss) | |
| I0331 15:54:25.434533 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.620471 (* 0.3 = 0.186141 loss) | |
| I0331 15:54:25.434561 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.391304 | |
| I0331 15:54:25.434574 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.829545 | |
| I0331 15:54:25.434587 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.673913 | |
| I0331 15:54:25.434600 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 1.8344 (* 0.3 = 0.550321 loss) | |
| I0331 15:54:25.434614 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.517046 (* 0.3 = 0.155114 loss) | |
| I0331 15:54:25.434626 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.478261 | |
| I0331 15:54:25.434639 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.857955 | |
| I0331 15:54:25.434651 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.782609 | |
| I0331 15:54:25.434665 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.57455 (* 1 = 1.57455 loss) | |
| I0331 15:54:25.434679 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.462591 (* 1 = 0.462591 loss) | |
| I0331 15:54:25.434690 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 15:54:25.434702 30833 solver.cpp:245] Train net output #16: total_confidence = 0.144367 | |
| I0331 15:54:25.434715 30833 sgd_solver.cpp:106] Iteration 25500, lr = 0.05 | |
| I0331 15:56:33.860862 30833 solver.cpp:229] Iteration 26000, loss = 3.70207 | |
| I0331 15:56:33.861094 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.272727 | |
| I0331 15:56:33.861114 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.772727 | |
| I0331 15:56:33.861125 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.431818 | |
| I0331 15:56:33.861141 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.67567 (* 0.3 = 0.802701 loss) | |
| I0331 15:56:33.861155 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.811129 (* 0.3 = 0.243339 loss) | |
| I0331 15:56:33.861168 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.431818 | |
| I0331 15:56:33.861179 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.823864 | |
| I0331 15:56:33.861191 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.636364 | |
| I0331 15:56:33.861204 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.18754 (* 0.3 = 0.656262 loss) | |
| I0331 15:56:33.861218 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.678535 (* 0.3 = 0.20356 loss) | |
| I0331 15:56:33.861230 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.545455 | |
| I0331 15:56:33.861243 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.869318 | |
| I0331 15:56:33.861253 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.681818 | |
| I0331 15:56:33.861268 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.56798 (* 1 = 1.56798 loss) | |
| I0331 15:56:33.861280 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.447297 (* 1 = 0.447297 loss) | |
| I0331 15:56:33.861292 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.25 | |
| I0331 15:56:33.861304 30833 solver.cpp:245] Train net output #16: total_confidence = 0.165023 | |
| I0331 15:56:33.861315 30833 sgd_solver.cpp:106] Iteration 26000, lr = 0.05 | |
| I0331 15:58:42.228175 30833 solver.cpp:229] Iteration 26500, loss = 3.75081 | |
| I0331 15:58:42.228332 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.255319 | |
| I0331 15:58:42.228359 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.789773 | |
| I0331 15:58:42.228373 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.617021 | |
| I0331 15:58:42.228387 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.22227 (* 0.3 = 0.666682 loss) | |
| I0331 15:58:42.228412 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.655958 (* 0.3 = 0.196788 loss) | |
| I0331 15:58:42.228430 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.319149 | |
| I0331 15:58:42.228442 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.801136 | |
| I0331 15:58:42.228454 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.702128 | |
| I0331 15:58:42.228467 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 1.8314 (* 0.3 = 0.549421 loss) | |
| I0331 15:58:42.228482 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.573278 (* 0.3 = 0.171984 loss) | |
| I0331 15:58:42.228493 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.659574 | |
| I0331 15:58:42.228505 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.897727 | |
| I0331 15:58:42.228516 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.87234 | |
| I0331 15:58:42.228530 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.11695 (* 1 = 1.11695 loss) | |
| I0331 15:58:42.228543 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.360001 (* 1 = 0.360001 loss) | |
| I0331 15:58:42.228555 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 15:58:42.228566 30833 solver.cpp:245] Train net output #16: total_confidence = 0.111043 | |
| I0331 15:58:42.228579 30833 sgd_solver.cpp:106] Iteration 26500, lr = 0.05 | |
| I0331 16:00:50.708986 30833 solver.cpp:229] Iteration 27000, loss = 3.71757 | |
| I0331 16:00:50.709108 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.2 | |
| I0331 16:00:50.709127 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.789773 | |
| I0331 16:00:50.709141 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.425 | |
| I0331 16:00:50.709156 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.63826 (* 0.3 = 0.791478 loss) | |
| I0331 16:00:50.709170 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.725623 (* 0.3 = 0.217687 loss) | |
| I0331 16:00:50.709182 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.3 | |
| I0331 16:00:50.709194 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.8125 | |
| I0331 16:00:50.709206 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.625 | |
| I0331 16:00:50.709219 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.24311 (* 0.3 = 0.672932 loss) | |
| I0331 16:00:50.709233 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.620121 (* 0.3 = 0.186036 loss) | |
| I0331 16:00:50.709245 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.65 | |
| I0331 16:00:50.709256 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.897727 | |
| I0331 16:00:50.709269 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.7 | |
| I0331 16:00:50.709281 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.36242 (* 1 = 1.36242 loss) | |
| I0331 16:00:50.709295 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.390177 (* 1 = 0.390177 loss) | |
| I0331 16:00:50.709307 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.125 | |
| I0331 16:00:50.709318 30833 solver.cpp:245] Train net output #16: total_confidence = 0.101959 | |
| I0331 16:00:50.709331 30833 sgd_solver.cpp:106] Iteration 27000, lr = 0.05 | |
| I0331 16:02:59.145120 30833 solver.cpp:229] Iteration 27500, loss = 3.70181 | |
| I0331 16:02:59.145265 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.288889 | |
| I0331 16:02:59.145284 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.801136 | |
| I0331 16:02:59.145298 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.488889 | |
| I0331 16:02:59.145313 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.87723 (* 0.3 = 0.863169 loss) | |
| I0331 16:02:59.145328 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.807726 (* 0.3 = 0.242318 loss) | |
| I0331 16:02:59.145347 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.4 | |
| I0331 16:02:59.145359 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.8125 | |
| I0331 16:02:59.145371 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.644444 | |
| I0331 16:02:59.145385 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.29594 (* 0.3 = 0.688782 loss) | |
| I0331 16:02:59.145406 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.689587 (* 0.3 = 0.206876 loss) | |
| I0331 16:02:59.145426 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.688889 | |
| I0331 16:02:59.145439 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.903409 | |
| I0331 16:02:59.145452 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.777778 | |
| I0331 16:02:59.145465 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.33471 (* 1 = 1.33471 loss) | |
| I0331 16:02:59.145480 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.412062 (* 1 = 0.412062 loss) | |
| I0331 16:02:59.145493 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.25 | |
| I0331 16:02:59.145504 30833 solver.cpp:245] Train net output #16: total_confidence = 0.130441 | |
| I0331 16:02:59.145516 30833 sgd_solver.cpp:106] Iteration 27500, lr = 0.05 | |
| I0331 16:05:07.450763 30833 solver.cpp:229] Iteration 28000, loss = 3.76232 | |
| I0331 16:05:07.450891 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.285714 | |
| I0331 16:05:07.450911 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.801136 | |
| I0331 16:05:07.450922 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.530612 | |
| I0331 16:05:07.450938 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.95022 (* 0.3 = 0.885065 loss) | |
| I0331 16:05:07.450953 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.870016 (* 0.3 = 0.261005 loss) | |
| I0331 16:05:07.450965 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.387755 | |
| I0331 16:05:07.450978 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.823864 | |
| I0331 16:05:07.450990 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.612245 | |
| I0331 16:05:07.451004 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.52162 (* 0.3 = 0.756487 loss) | |
| I0331 16:05:07.451017 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.74434 (* 0.3 = 0.223302 loss) | |
| I0331 16:05:07.451030 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.571429 | |
| I0331 16:05:07.451041 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.857955 | |
| I0331 16:05:07.451052 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.714286 | |
| I0331 16:05:07.451066 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.73004 (* 1 = 1.73004 loss) | |
| I0331 16:05:07.451105 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.545703 (* 1 = 0.545703 loss) | |
| I0331 16:05:07.451133 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.125 | |
| I0331 16:05:07.451165 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0850027 | |
| I0331 16:05:07.451187 30833 sgd_solver.cpp:106] Iteration 28000, lr = 0.05 | |
| I0331 16:07:15.901681 30833 solver.cpp:229] Iteration 28500, loss = 3.70106 | |
| I0331 16:07:15.901825 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.27027 | |
| I0331 16:07:15.901845 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.778409 | |
| I0331 16:07:15.901865 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.540541 | |
| I0331 16:07:15.901881 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.37819 (* 0.3 = 0.713457 loss) | |
| I0331 16:07:15.901896 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.744204 (* 0.3 = 0.223261 loss) | |
| I0331 16:07:15.901909 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.351351 | |
| I0331 16:07:15.901921 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.795455 | |
| I0331 16:07:15.901933 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.648649 | |
| I0331 16:07:15.901947 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.13 (* 0.3 = 0.638999 loss) | |
| I0331 16:07:15.901960 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.689803 (* 0.3 = 0.206941 loss) | |
| I0331 16:07:15.901973 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.702703 | |
| I0331 16:07:15.901983 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.909091 | |
| I0331 16:07:15.901995 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.810811 | |
| I0331 16:07:15.902009 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.04427 (* 1 = 1.04427 loss) | |
| I0331 16:07:15.902022 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.347893 (* 1 = 0.347893 loss) | |
| I0331 16:07:15.902034 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.25 | |
| I0331 16:07:15.902045 30833 solver.cpp:245] Train net output #16: total_confidence = 0.251065 | |
| I0331 16:07:15.902057 30833 sgd_solver.cpp:106] Iteration 28500, lr = 0.05 | |
| I0331 16:09:24.288419 30833 solver.cpp:229] Iteration 29000, loss = 3.68289 | |
| I0331 16:09:24.288533 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.269231 | |
| I0331 16:09:24.288553 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.778409 | |
| I0331 16:09:24.288565 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.461538 | |
| I0331 16:09:24.288581 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.59602 (* 0.3 = 0.778806 loss) | |
| I0331 16:09:24.288595 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.797424 (* 0.3 = 0.239227 loss) | |
| I0331 16:09:24.288609 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.288462 | |
| I0331 16:09:24.288620 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.784091 | |
| I0331 16:09:24.288631 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.538462 | |
| I0331 16:09:24.288645 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.42306 (* 0.3 = 0.726919 loss) | |
| I0331 16:09:24.288660 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.746727 (* 0.3 = 0.224018 loss) | |
| I0331 16:09:24.288671 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.480769 | |
| I0331 16:09:24.288682 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.835227 | |
| I0331 16:09:24.288693 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.711538 | |
| I0331 16:09:24.288707 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.76042 (* 1 = 1.76042 loss) | |
| I0331 16:09:24.288720 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.560407 (* 1 = 0.560407 loss) | |
| I0331 16:09:24.288733 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.125 | |
| I0331 16:09:24.288744 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0924889 | |
| I0331 16:09:24.288756 30833 sgd_solver.cpp:106] Iteration 29000, lr = 0.05 | |
| I0331 16:11:33.050727 30833 solver.cpp:229] Iteration 29500, loss = 3.62499 | |
| I0331 16:11:33.050876 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.276596 | |
| I0331 16:11:33.050904 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.795455 | |
| I0331 16:11:33.050916 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.510638 | |
| I0331 16:11:33.050931 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.39411 (* 0.3 = 0.718235 loss) | |
| I0331 16:11:33.050956 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.704153 (* 0.3 = 0.211246 loss) | |
| I0331 16:11:33.050967 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.489362 | |
| I0331 16:11:33.050979 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.863636 | |
| I0331 16:11:33.050992 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.680851 | |
| I0331 16:11:33.051004 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 1.90896 (* 0.3 = 0.572688 loss) | |
| I0331 16:11:33.051018 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.546237 (* 0.3 = 0.163871 loss) | |
| I0331 16:11:33.051030 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.638298 | |
| I0331 16:11:33.051041 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.869318 | |
| I0331 16:11:33.051054 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.744681 | |
| I0331 16:11:33.051066 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.35217 (* 1 = 1.35217 loss) | |
| I0331 16:11:33.051080 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.471177 (* 1 = 0.471177 loss) | |
| I0331 16:11:33.051110 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.125 | |
| I0331 16:11:33.051121 30833 solver.cpp:245] Train net output #16: total_confidence = 0.134925 | |
| I0331 16:11:33.051133 30833 sgd_solver.cpp:106] Iteration 29500, lr = 0.05 | |
| I0331 16:13:41.771999 30833 solver.cpp:338] Iteration 30000, Testing net (#0) | |
| I0331 16:14:11.532569 30833 solver.cpp:393] Test loss: 3.21744 | |
| I0331 16:14:11.532618 30833 solver.cpp:406] Test net output #0: loss1/accuracy = 0.380815 | |
| I0331 16:14:11.532634 30833 solver.cpp:406] Test net output #1: loss1/accuracy_incl_empty = 0.841139 | |
| I0331 16:14:11.532647 30833 solver.cpp:406] Test net output #2: loss1/accuracy_top3 = 0.661215 | |
| I0331 16:14:11.532662 30833 solver.cpp:406] Test net output #3: loss1/cross_entropy_loss = 2.1839 (* 0.3 = 0.655169 loss) | |
| I0331 16:14:11.532677 30833 solver.cpp:406] Test net output #4: loss1/cross_entropy_loss_incl_empty = 0.567265 (* 0.3 = 0.170179 loss) | |
| I0331 16:14:11.532690 30833 solver.cpp:406] Test net output #5: loss2/accuracy = 0.485388 | |
| I0331 16:14:11.532701 30833 solver.cpp:406] Test net output #6: loss2/accuracy_incl_empty = 0.871867 | |
| I0331 16:14:11.532712 30833 solver.cpp:406] Test net output #7: loss2/accuracy_top3 = 0.776283 | |
| I0331 16:14:11.532726 30833 solver.cpp:406] Test net output #8: loss2/cross_entropy_loss = 1.7742 (* 0.3 = 0.532259 loss) | |
| I0331 16:14:11.532739 30833 solver.cpp:406] Test net output #9: loss2/cross_entropy_loss_incl_empty = 0.447147 (* 0.3 = 0.134144 loss) | |
| I0331 16:14:11.532750 30833 solver.cpp:406] Test net output #10: loss3/accuracy = 0.649869 | |
| I0331 16:14:11.532763 30833 solver.cpp:406] Test net output #11: loss3/accuracy_incl_empty = 0.91182 | |
| I0331 16:14:11.532773 30833 solver.cpp:406] Test net output #12: loss3/accuracy_top3 = 0.834636 | |
| I0331 16:14:11.532786 30833 solver.cpp:406] Test net output #13: loss3/cross_entropy_loss = 1.37575 (* 1 = 1.37575 loss) | |
| I0331 16:14:11.532799 30833 solver.cpp:406] Test net output #14: loss3/cross_entropy_loss_incl_empty = 0.349943 (* 1 = 0.349943 loss) | |
| I0331 16:14:11.532811 30833 solver.cpp:406] Test net output #15: total_accuracy = 0.218 | |
| I0331 16:14:11.532822 30833 solver.cpp:406] Test net output #16: total_confidence = 0.302196 | |
| I0331 16:14:11.683243 30833 solver.cpp:229] Iteration 30000, loss = 3.68079 | |
| I0331 16:14:11.683284 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.1875 | |
| I0331 16:14:11.683300 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.767045 | |
| I0331 16:14:11.683312 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.479167 | |
| I0331 16:14:11.683327 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.61592 (* 0.3 = 0.784776 loss) | |
| I0331 16:14:11.683342 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.782977 (* 0.3 = 0.234893 loss) | |
| I0331 16:14:11.683356 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.166667 | |
| I0331 16:14:11.683367 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.767045 | |
| I0331 16:14:11.683379 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.479167 | |
| I0331 16:14:11.683393 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.54401 (* 0.3 = 0.763202 loss) | |
| I0331 16:14:11.683406 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.728053 (* 0.3 = 0.218416 loss) | |
| I0331 16:14:11.683418 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.458333 | |
| I0331 16:14:11.683430 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.840909 | |
| I0331 16:14:11.683441 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.666667 | |
| I0331 16:14:11.683455 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.90671 (* 1 = 1.90671 loss) | |
| I0331 16:14:11.683468 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.557145 (* 1 = 0.557145 loss) | |
| I0331 16:14:11.683480 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.125 | |
| I0331 16:14:11.683492 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0364392 | |
| I0331 16:14:11.683504 30833 sgd_solver.cpp:106] Iteration 30000, lr = 0.05 | |
| I0331 16:16:19.920083 30833 solver.cpp:229] Iteration 30500, loss = 3.58471 | |
| I0331 16:16:19.920402 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.288889 | |
| I0331 16:16:19.920421 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.818182 | |
| I0331 16:16:19.920434 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.488889 | |
| I0331 16:16:19.920450 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.46769 (* 0.3 = 0.740306 loss) | |
| I0331 16:16:19.920465 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.663631 (* 0.3 = 0.199089 loss) | |
| I0331 16:16:19.920477 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.333333 | |
| I0331 16:16:19.920490 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.818182 | |
| I0331 16:16:19.920501 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.577778 | |
| I0331 16:16:19.920514 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.26749 (* 0.3 = 0.680247 loss) | |
| I0331 16:16:19.920528 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.641335 (* 0.3 = 0.1924 loss) | |
| I0331 16:16:19.920542 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.533333 | |
| I0331 16:16:19.920552 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.863636 | |
| I0331 16:16:19.920564 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.822222 | |
| I0331 16:16:19.920578 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.30236 (* 1 = 1.30236 loss) | |
| I0331 16:16:19.920591 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.370069 (* 1 = 0.370069 loss) | |
| I0331 16:16:19.920603 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.125 | |
| I0331 16:16:19.920614 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0922499 | |
| I0331 16:16:19.920626 30833 sgd_solver.cpp:106] Iteration 30500, lr = 0.05 | |
| I0331 16:18:28.355360 30833 solver.cpp:229] Iteration 31000, loss = 3.64064 | |
| I0331 16:18:28.355505 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.358974 | |
| I0331 16:18:28.355525 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.835227 | |
| I0331 16:18:28.355545 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.564103 | |
| I0331 16:18:28.355561 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.32839 (* 0.3 = 0.698517 loss) | |
| I0331 16:18:28.355587 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.633988 (* 0.3 = 0.190196 loss) | |
| I0331 16:18:28.355602 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.307692 | |
| I0331 16:18:28.355614 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.823864 | |
| I0331 16:18:28.355626 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.512821 | |
| I0331 16:18:28.355640 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.1961 (* 0.3 = 0.658829 loss) | |
| I0331 16:18:28.355654 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.613052 (* 0.3 = 0.183915 loss) | |
| I0331 16:18:28.355666 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.487179 | |
| I0331 16:18:28.355679 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.875 | |
| I0331 16:18:28.355690 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.692308 | |
| I0331 16:18:28.355703 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.5043 (* 1 = 1.5043 loss) | |
| I0331 16:18:28.355717 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.391891 (* 1 = 0.391891 loss) | |
| I0331 16:18:28.355728 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.125 | |
| I0331 16:18:28.355741 30833 solver.cpp:245] Train net output #16: total_confidence = 0.159545 | |
| I0331 16:18:28.355752 30833 sgd_solver.cpp:106] Iteration 31000, lr = 0.05 | |
| I0331 16:20:36.468720 30833 solver.cpp:229] Iteration 31500, loss = 3.62638 | |
| I0331 16:20:36.468852 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.282609 | |
| I0331 16:20:36.468880 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.789773 | |
| I0331 16:20:36.468902 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.586957 | |
| I0331 16:20:36.468940 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.36468 (* 0.3 = 0.709403 loss) | |
| I0331 16:20:36.468971 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.70644 (* 0.3 = 0.211932 loss) | |
| I0331 16:20:36.468986 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.391304 | |
| I0331 16:20:36.468998 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.8125 | |
| I0331 16:20:36.469009 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.76087 | |
| I0331 16:20:36.469023 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 1.978 (* 0.3 = 0.5934 loss) | |
| I0331 16:20:36.469038 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.628851 (* 0.3 = 0.188655 loss) | |
| I0331 16:20:36.469051 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.630435 | |
| I0331 16:20:36.469063 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.886364 | |
| I0331 16:20:36.469074 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.73913 | |
| I0331 16:20:36.469090 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.38627 (* 1 = 1.38627 loss) | |
| I0331 16:20:36.469105 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.433005 (* 1 = 0.433005 loss) | |
| I0331 16:20:36.469116 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.25 | |
| I0331 16:20:36.469128 30833 solver.cpp:245] Train net output #16: total_confidence = 0.144842 | |
| I0331 16:20:36.469140 30833 sgd_solver.cpp:106] Iteration 31500, lr = 0.05 | |
| I0331 16:22:44.924576 30833 solver.cpp:229] Iteration 32000, loss = 3.60735 | |
| I0331 16:22:44.924718 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.452381 | |
| I0331 16:22:44.924739 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.840909 | |
| I0331 16:22:44.924759 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.714286 | |
| I0331 16:22:44.924775 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.07783 (* 0.3 = 0.623348 loss) | |
| I0331 16:22:44.924790 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.582335 (* 0.3 = 0.174701 loss) | |
| I0331 16:22:44.924803 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.452381 | |
| I0331 16:22:44.924815 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.852273 | |
| I0331 16:22:44.924826 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.785714 | |
| I0331 16:22:44.924840 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 1.92358 (* 0.3 = 0.577074 loss) | |
| I0331 16:22:44.924854 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.522393 (* 0.3 = 0.156718 loss) | |
| I0331 16:22:44.924866 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.761905 | |
| I0331 16:22:44.924878 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.926136 | |
| I0331 16:22:44.924890 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.857143 | |
| I0331 16:22:44.924903 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 0.873023 (* 1 = 0.873023 loss) | |
| I0331 16:22:44.924917 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.251158 (* 1 = 0.251158 loss) | |
| I0331 16:22:44.924929 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.5 | |
| I0331 16:22:44.924940 30833 solver.cpp:245] Train net output #16: total_confidence = 0.313801 | |
| I0331 16:22:44.924952 30833 sgd_solver.cpp:106] Iteration 32000, lr = 0.05 | |
| I0331 16:24:53.261831 30833 solver.cpp:229] Iteration 32500, loss = 3.55733 | |
| I0331 16:24:53.261946 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.235294 | |
| I0331 16:24:53.261966 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.772727 | |
| I0331 16:24:53.261978 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.529412 | |
| I0331 16:24:53.261994 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.73332 (* 0.3 = 0.819997 loss) | |
| I0331 16:24:53.262009 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.830469 (* 0.3 = 0.249141 loss) | |
| I0331 16:24:53.262022 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.352941 | |
| I0331 16:24:53.262033 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.8125 | |
| I0331 16:24:53.262045 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.588235 | |
| I0331 16:24:53.262058 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.46311 (* 0.3 = 0.738934 loss) | |
| I0331 16:24:53.262073 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.7315 (* 0.3 = 0.21945 loss) | |
| I0331 16:24:53.262087 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.627451 | |
| I0331 16:24:53.262099 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.869318 | |
| I0331 16:24:53.262111 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.862745 | |
| I0331 16:24:53.262125 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.51577 (* 1 = 1.51577 loss) | |
| I0331 16:24:53.262140 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.486409 (* 1 = 0.486409 loss) | |
| I0331 16:24:53.262151 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.125 | |
| I0331 16:24:53.262162 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0643552 | |
| I0331 16:24:53.262174 30833 sgd_solver.cpp:106] Iteration 32500, lr = 0.05 | |
| I0331 16:27:01.625883 30833 solver.cpp:229] Iteration 33000, loss = 3.50032 | |
| I0331 16:27:01.626036 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.363636 | |
| I0331 16:27:01.626057 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.823864 | |
| I0331 16:27:01.626078 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.477273 | |
| I0331 16:27:01.626096 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.30524 (* 0.3 = 0.691571 loss) | |
| I0331 16:27:01.626114 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.667098 (* 0.3 = 0.200129 loss) | |
| I0331 16:27:01.626128 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.340909 | |
| I0331 16:27:01.626142 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.818182 | |
| I0331 16:27:01.626152 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.659091 | |
| I0331 16:27:01.626166 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.0353 (* 0.3 = 0.610589 loss) | |
| I0331 16:27:01.626180 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.559049 (* 0.3 = 0.167715 loss) | |
| I0331 16:27:01.626193 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.477273 | |
| I0331 16:27:01.626204 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.857955 | |
| I0331 16:27:01.626215 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.840909 | |
| I0331 16:27:01.626230 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.47184 (* 1 = 1.47184 loss) | |
| I0331 16:27:01.626243 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.405841 (* 1 = 0.405841 loss) | |
| I0331 16:27:01.626262 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 16:27:01.626274 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0664544 | |
| I0331 16:27:01.626286 30833 sgd_solver.cpp:106] Iteration 33000, lr = 0.05 | |
| I0331 16:29:10.065448 30833 solver.cpp:229] Iteration 33500, loss = 3.57174 | |
| I0331 16:29:10.065558 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.25 | |
| I0331 16:29:10.065577 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.795455 | |
| I0331 16:29:10.065590 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.477273 | |
| I0331 16:29:10.065606 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.52785 (* 0.3 = 0.758356 loss) | |
| I0331 16:29:10.065621 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.699578 (* 0.3 = 0.209874 loss) | |
| I0331 16:29:10.065634 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.363636 | |
| I0331 16:29:10.065647 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.818182 | |
| I0331 16:29:10.065659 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.636364 | |
| I0331 16:29:10.065672 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.26156 (* 0.3 = 0.678468 loss) | |
| I0331 16:29:10.065686 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.640423 (* 0.3 = 0.192127 loss) | |
| I0331 16:29:10.065698 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.431818 | |
| I0331 16:29:10.065709 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.846591 | |
| I0331 16:29:10.065721 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.659091 | |
| I0331 16:29:10.065734 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.90563 (* 1 = 1.90563 loss) | |
| I0331 16:29:10.065748 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.525037 (* 1 = 0.525037 loss) | |
| I0331 16:29:10.065759 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.125 | |
| I0331 16:29:10.065771 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0561105 | |
| I0331 16:29:10.065783 30833 sgd_solver.cpp:106] Iteration 33500, lr = 0.05 | |
| I0331 16:31:18.417491 30833 solver.cpp:229] Iteration 34000, loss = 3.48928 | |
| I0331 16:31:18.417639 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.325 | |
| I0331 16:31:18.417659 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.784091 | |
| I0331 16:31:18.417678 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.475 | |
| I0331 16:31:18.417695 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.31951 (* 0.3 = 0.695854 loss) | |
| I0331 16:31:18.417709 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.755554 (* 0.3 = 0.226666 loss) | |
| I0331 16:31:18.417721 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.425 | |
| I0331 16:31:18.417733 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.806818 | |
| I0331 16:31:18.417744 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.7 | |
| I0331 16:31:18.417758 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 1.98126 (* 0.3 = 0.594379 loss) | |
| I0331 16:31:18.417773 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.641614 (* 0.3 = 0.192484 loss) | |
| I0331 16:31:18.417784 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.725 | |
| I0331 16:31:18.417795 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.914773 | |
| I0331 16:31:18.417807 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.875 | |
| I0331 16:31:18.417820 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.293 (* 1 = 1.293 loss) | |
| I0331 16:31:18.417834 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.356172 (* 1 = 0.356172 loss) | |
| I0331 16:31:18.417845 30833 solver.cpp:245] Train net output #15: total_accuracy = 0.25 | |
| I0331 16:31:18.417857 30833 solver.cpp:245] Train net output #16: total_confidence = 0.285068 | |
| I0331 16:31:18.417868 30833 sgd_solver.cpp:106] Iteration 34000, lr = 0.05 | |
| I0331 16:33:26.869297 30833 solver.cpp:229] Iteration 34500, loss = 3.52718 | |
| I0331 16:33:26.869401 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.265306 | |
| I0331 16:33:26.869421 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.778409 | |
| I0331 16:33:26.869432 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.469388 | |
| I0331 16:33:26.869448 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.73983 (* 0.3 = 0.82195 loss) | |
| I0331 16:33:26.869463 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.830486 (* 0.3 = 0.249146 loss) | |
| I0331 16:33:26.869475 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.469388 | |
| I0331 16:33:26.869488 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.840909 | |
| I0331 16:33:26.869499 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.632653 | |
| I0331 16:33:26.869513 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.09497 (* 0.3 = 0.62849 loss) | |
| I0331 16:33:26.869527 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.634349 (* 0.3 = 0.190305 loss) | |
| I0331 16:33:26.869539 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.44898 | |
| I0331 16:33:26.869559 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.840909 | |
| I0331 16:33:26.869570 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.653061 | |
| I0331 16:33:26.869587 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.91852 (* 1 = 1.91852 loss) | |
| I0331 16:33:26.869612 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.557778 (* 1 = 0.557778 loss) | |
| I0331 16:33:26.869626 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 16:33:26.869637 30833 solver.cpp:245] Train net output #16: total_confidence = 0.191329 | |
| I0331 16:33:26.869649 30833 sgd_solver.cpp:106] Iteration 34500, lr = 0.05 | |
| I0331 16:35:36.074234 30833 solver.cpp:338] Iteration 35000, Testing net (#0) | |
| I0331 16:36:05.617636 30833 solver.cpp:393] Test loss: 2.98348 | |
| I0331 16:36:05.617694 30833 solver.cpp:406] Test net output #0: loss1/accuracy = 0.407317 | |
| I0331 16:36:05.617710 30833 solver.cpp:406] Test net output #1: loss1/accuracy_incl_empty = 0.838412 | |
| I0331 16:36:05.617722 30833 solver.cpp:406] Test net output #2: loss1/accuracy_top3 = 0.673205 | |
| I0331 16:36:05.617738 30833 solver.cpp:406] Test net output #3: loss1/cross_entropy_loss = 2.07123 (* 0.3 = 0.62137 loss) | |
| I0331 16:36:05.617753 30833 solver.cpp:406] Test net output #4: loss1/cross_entropy_loss_incl_empty = 0.578037 (* 0.3 = 0.173411 loss) | |
| I0331 16:36:05.617764 30833 solver.cpp:406] Test net output #5: loss2/accuracy = 0.554664 | |
| I0331 16:36:05.617776 30833 solver.cpp:406] Test net output #6: loss2/accuracy_incl_empty = 0.880821 | |
| I0331 16:36:05.617787 30833 solver.cpp:406] Test net output #7: loss2/accuracy_top3 = 0.800434 | |
| I0331 16:36:05.617800 30833 solver.cpp:406] Test net output #8: loss2/cross_entropy_loss = 1.56205 (* 0.3 = 0.468616 loss) | |
| I0331 16:36:05.617813 30833 solver.cpp:406] Test net output #9: loss2/cross_entropy_loss_incl_empty = 0.42163 (* 0.3 = 0.126489 loss) | |
| I0331 16:36:05.617825 30833 solver.cpp:406] Test net output #10: loss3/accuracy = 0.694184 | |
| I0331 16:36:05.617837 30833 solver.cpp:406] Test net output #11: loss3/accuracy_incl_empty = 0.919683 | |
| I0331 16:36:05.617848 30833 solver.cpp:406] Test net output #12: loss3/accuracy_top3 = 0.846168 | |
| I0331 16:36:05.617861 30833 solver.cpp:406] Test net output #13: loss3/cross_entropy_loss = 1.26305 (* 1 = 1.26305 loss) | |
| I0331 16:36:05.617874 30833 solver.cpp:406] Test net output #14: loss3/cross_entropy_loss_incl_empty = 0.330542 (* 1 = 0.330542 loss) | |
| I0331 16:36:05.617887 30833 solver.cpp:406] Test net output #15: total_accuracy = 0.302 | |
| I0331 16:36:05.617897 30833 solver.cpp:406] Test net output #16: total_confidence = 0.319886 | |
| I0331 16:36:05.768681 30833 solver.cpp:229] Iteration 35000, loss = 3.53365 | |
| I0331 16:36:05.768721 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.285714 | |
| I0331 16:36:05.768738 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.806818 | |
| I0331 16:36:05.768749 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.357143 | |
| I0331 16:36:05.768764 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.84044 (* 0.3 = 0.852131 loss) | |
| I0331 16:36:05.768779 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.783073 (* 0.3 = 0.234922 loss) | |
| I0331 16:36:05.768791 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.214286 | |
| I0331 16:36:05.768803 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.778409 | |
| I0331 16:36:05.768815 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.5 | |
| I0331 16:36:05.768828 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.65415 (* 0.3 = 0.796246 loss) | |
| I0331 16:36:05.768842 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.749453 (* 0.3 = 0.224836 loss) | |
| I0331 16:36:05.768853 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.333333 | |
| I0331 16:36:05.768865 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.818182 | |
| I0331 16:36:05.768877 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.571429 | |
| I0331 16:36:05.768890 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 2.26016 (* 1 = 2.26016 loss) | |
| I0331 16:36:05.768904 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.652646 (* 1 = 0.652646 loss) | |
| I0331 16:36:05.768916 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 16:36:05.768928 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0465938 | |
| I0331 16:36:05.768940 30833 sgd_solver.cpp:106] Iteration 35000, lr = 0.05 | |
| I0331 16:38:14.303848 30833 solver.cpp:229] Iteration 35500, loss = 3.48919 | |
| I0331 16:38:14.303992 30833 solver.cpp:245] Train net output #0: loss1/accuracy = 0.333333 | |
| I0331 16:38:14.304011 30833 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.835227 | |
| I0331 16:38:14.304033 30833 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.564103 | |
| I0331 16:38:14.304049 30833 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 2.3691 (* 0.3 = 0.710731 loss) | |
| I0331 16:38:14.304062 30833 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 0.639052 (* 0.3 = 0.191716 loss) | |
| I0331 16:38:14.304075 30833 solver.cpp:245] Train net output #5: loss2/accuracy = 0.384615 | |
| I0331 16:38:14.304087 30833 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0.835227 | |
| I0331 16:38:14.304098 30833 solver.cpp:245] Train net output #7: loss2/accuracy_top3 = 0.615385 | |
| I0331 16:38:14.304113 30833 solver.cpp:245] Train net output #8: loss2/cross_entropy_loss = 2.12196 (* 0.3 = 0.636587 loss) | |
| I0331 16:38:14.304127 30833 solver.cpp:245] Train net output #9: loss2/cross_entropy_loss_incl_empty = 0.608983 (* 0.3 = 0.182695 loss) | |
| I0331 16:38:14.304138 30833 solver.cpp:245] Train net output #10: loss3/accuracy = 0.512821 | |
| I0331 16:38:14.304150 30833 solver.cpp:245] Train net output #11: loss3/accuracy_incl_empty = 0.875 | |
| I0331 16:38:14.304162 30833 solver.cpp:245] Train net output #12: loss3/accuracy_top3 = 0.74359 | |
| I0331 16:38:14.304182 30833 solver.cpp:245] Train net output #13: loss3/cross_entropy_loss = 1.53808 (* 1 = 1.53808 loss) | |
| I0331 16:38:14.304194 30833 solver.cpp:245] Train net output #14: loss3/cross_entropy_loss_incl_empty = 0.393185 (* 1 = 0.393185 loss) | |
| I0331 16:38:14.304206 30833 solver.cpp:245] Train net output #15: total_accuracy = 0 | |
| I0331 16:38:14.304217 30833 solver.cpp:245] Train net output #16: total_confidence = 0.0559362 | |
| I0331 16:38:14.304229 30833 sgd_solver.cpp:106] Iteration 35500, lr = 0.05 | |
| I0331 16:40:22.661485 30833 solver.cpp:229] Iteration 36000, loss = 3.48891 |
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