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stas-sl
/ firenet150x50_len22_4_trainval
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April 5, 2016 19:56
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| I0405 13:48:26.366220 29564 solver.cpp:280] Solving | |
| I0405 13:48:26.366231 29564 solver.cpp:281] Learning Rate Policy: poly | |
| I0405 13:48:26.526338 29564 solver.cpp:229] Iteration 0, loss = 4.30412 | |
| I0405 13:48:26.526379 29564 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0405 13:48:26.526397 29564 solver.cpp:245] Train net output #1: loss/accuracy02 = 0.03125 | |
| I0405 13:48:26.526412 29564 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0405 13:48:26.526423 29564 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0405 13:48:26.526435 29564 solver.cpp:245] Train net output #4: loss/accuracy05 = 0.03125 | |
| I0405 13:48:26.526448 29564 solver.cpp:245] Train net output #5: loss/accuracy06 = 0 | |
| I0405 13:48:26.526459 29564 solver.cpp:245] Train net output #6: loss/accuracy07 = 0 |
stas-sl
/ firenet150x50_len22_3_trainval
Last active
April 5, 2016 10:45
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| I0404 23:42:02.924360 26022 solver.cpp:280] Solving | |
| I0404 23:42:02.924372 26022 solver.cpp:281] Learning Rate Policy: poly | |
| I0404 23:42:13.433935 26022 solver.cpp:229] Iteration 0, loss = 4.304 | |
| I0404 23:42:13.433985 26022 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0404 23:42:13.434006 26022 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0404 23:42:13.434020 26022 solver.cpp:245] Train net output #2: loss/accuracy03 = 0 | |
| I0404 23:42:13.434031 26022 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0404 23:42:13.434043 26022 solver.cpp:245] Train net output #4: loss/accuracy05 = 0 | |
| I0404 23:42:13.434056 26022 solver.cpp:245] Train net output #5: loss/accuracy06 = 0 | |
| I0404 23:42:13.434067 26022 solver.cpp:245] Train net output #6: loss/accuracy07 = 0 |
stas-sl
/ firenet150x50_len22_2_trainval
Last active
April 4, 2016 17:21
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| I0404 12:49:59.854396 9252 solver.cpp:280] Solving | |
| I0404 12:49:59.854408 9252 solver.cpp:281] Learning Rate Policy: poly | |
| I0404 12:49:59.914067 9252 solver.cpp:229] Iteration 0, loss = 4.30411 | |
| I0404 12:49:59.914113 9252 solver.cpp:245] Train net output #0: loss/accuracy01 = 0 | |
| I0404 12:49:59.914134 9252 solver.cpp:245] Train net output #1: loss/accuracy02 = 0 | |
| I0404 12:49:59.914146 9252 solver.cpp:245] Train net output #2: loss/accuracy03 = 0.0625 | |
| I0404 12:49:59.914160 9252 solver.cpp:245] Train net output #3: loss/accuracy04 = 0 | |
| I0404 12:49:59.914171 9252 solver.cpp:245] Train net output #4: loss/accuracy05 = 0 | |
| I0404 12:49:59.914182 9252 solver.cpp:245] Train net output #5: loss/accuracy06 = 0 | |
| I0404 12:49:59.914193 9252 solver.cpp:245] Train net output #6: loss/accuracy07 = 0 |
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| I0401 12:44:49.957870 6134 solver.cpp:280] Solving mixed_lstm | |
| I0401 12:44:49.957882 6134 solver.cpp:281] Learning Rate Policy: fixed | |
| I0401 12:44:50.306246 6134 solver.cpp:229] Iteration 0, loss = 13.7773 | |
| I0401 12:44:50.306291 6134 solver.cpp:245] Train net output #0: loss1/accuracy = 0 | |
| I0401 12:44:50.306309 6134 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0.181818 | |
| I0401 12:44:50.306321 6134 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.0222222 | |
| I0401 12:44:50.306339 6134 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 4.39462 (* 0.3 = 1.31839 loss) | |
| I0401 12:44:50.306352 6134 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 4.19871 (* 0.3 = 1.25961 loss) | |
| I0401 12:44:50.306365 6134 solver.cpp:245] Train net output #5: loss2/accuracy = 0 | |
| I0401 12:44:50.306397 6134 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0 |
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| I0401 10:07:22.297281 31447 solver.cpp:280] Solving mixed_lstm | |
| I0401 10:07:22.297292 31447 solver.cpp:281] Learning Rate Policy: fixed | |
| I0401 10:07:22.643712 31447 solver.cpp:229] Iteration 0, loss = 14.0021 | |
| I0401 10:07:22.643754 31447 solver.cpp:245] Train net output #0: loss1/accuracy = 0 | |
| I0401 10:07:22.643769 31447 solver.cpp:245] Train net output #1: loss1/accuracy_incl_empty = 0 | |
| I0401 10:07:22.643782 31447 solver.cpp:245] Train net output #2: loss1/accuracy_top3 = 0.0238095 | |
| I0401 10:07:22.643798 31447 solver.cpp:245] Train net output #3: loss1/cross_entropy_loss = 4.45928 (* 0.3 = 1.33778 loss) | |
| I0401 10:07:22.643812 31447 solver.cpp:245] Train net output #4: loss1/cross_entropy_loss_incl_empty = 4.36399 (* 0.3 = 1.3092 loss) | |
| I0401 10:07:22.643826 31447 solver.cpp:245] Train net output #5: loss2/accuracy = 0 | |
| I0401 10:07:22.643837 31447 solver.cpp:245] Train net output #6: loss2/accuracy_incl_empty = 0 |
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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 |
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| I0330 00:58:47.679792 10583 solver.cpp:280] Solving mixed_lstm | |
| I0330 00:58:47.679805 10583 solver.cpp:281] Learning Rate Policy: fixed | |
| I0330 00:58:47.700913 10583 solver.cpp:338] Iteration 0, Testing net (#0) | |
| I0330 00:59:21.332644 10583 solver.cpp:393] Test loss: 272.275 | |
| I0330 00:59:21.333082 10583 solver.cpp:406] Test net output #0: loss1/accuracy = 0.0014 | |
| I0330 00:59:21.333103 10583 solver.cpp:406] Test net output #1: loss1/accuracy_incl_empty = 0.664909 | |
| I0330 00:59:21.333117 10583 solver.cpp:406] Test net output #2: loss1/accuracy_top3 = 0.00426905 | |
| I0330 00:59:21.333134 10583 solver.cpp:406] Test net output #3: loss1/cross_entropy_loss = 75.728 (* 0.3 = 22.7184 loss) | |
| I0330 00:59:21.333150 10583 solver.cpp:406] Test net output #4: loss1/cross_entropy_loss_incl_empty = 75.7553 (* 0.3 = 22.7266 loss) | |
| I0330 00:59:21.333165 10583 solver.cpp:406] Test net output #5: loss2/accuracy = 0 |
stas-sl
/ caffe.ip-172-31-38-100.invalid-user.log.INFO.20160330-005805.10583
Created
March 30, 2016 07:26
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| Log file created at: 2016/03/30 00:58:05 | |
| Running on machine: ip-172-31-38-100 | |
| Log line format: [IWEF]mmdd hh:mm:ss.uuuuuu threadid file:line] msg | |
| I0330 00:58:05.628971 10583 caffe.cpp:185] Using GPUs 0 | |
| I0330 00:58:05.885462 10583 caffe.cpp:190] GPU 0: GRID K520 | |
| I0330 00:58:06.003937 10583 solver.cpp:48] Initializing solver from parameters: | |
| test_iter: 1000 | |
| test_interval: 5000 | |
| base_lr: 0.01 | |
| display: 500 |
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| I0327 12:46:12.071159 21344 solver.cpp:280] Solving mixed_lstm | |
| I0327 12:46:12.071171 21344 solver.cpp:281] Learning Rate Policy: fixed | |
| I0327 12:46:12.088115 21344 solver.cpp:338] Iteration 0, Testing net (#0) | |
| I0327 12:46:43.353196 21344 solver.cpp:393] Test loss: 256.606 | |
| I0327 12:46:43.353467 21344 solver.cpp:406] Test net output #0: loss1/accuracy01 = 0.002 | |
| I0327 12:46:43.353493 21344 solver.cpp:406] Test net output #1: loss1/accuracy02 = 0.008 | |
| I0327 12:46:43.353507 21344 solver.cpp:406] Test net output #2: loss1/accuracy03 = 0.018 | |
| I0327 12:46:43.353519 21344 solver.cpp:406] Test net output #3: loss1/accuracy04 = 0.037 | |
| I0327 12:46:43.353531 21344 solver.cpp:406] Test net output #4: loss1/accuracy05 = 0.049 | |
| I0327 12:46:43.353559 21344 solver.cpp:406] Test net output #5: loss1/accuracy06 = 0.136 |
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| I0327 12:46:12.071159 21344 solver.cpp:280] Solving mixed_lstm | |
| I0327 12:46:12.071171 21344 solver.cpp:281] Learning Rate Policy: fixed | |
| I0327 12:46:12.088115 21344 solver.cpp:338] Iteration 0, Testing net (#0) | |
| I0327 12:46:43.353196 21344 solver.cpp:393] Test loss: 256.606 | |
| I0327 12:46:43.353467 21344 solver.cpp:406] Test net output #0: loss1/accuracy01 = 0.002 | |
| I0327 12:46:43.353493 21344 solver.cpp:406] Test net output #1: loss1/accuracy02 = 0.008 | |
| I0327 12:46:43.353507 21344 solver.cpp:406] Test net output #2: loss1/accuracy03 = 0.018 | |
| I0327 12:46:43.353519 21344 solver.cpp:406] Test net output #3: loss1/accuracy04 = 0.037 | |
| I0327 12:46:43.353531 21344 solver.cpp:406] Test net output #4: loss1/accuracy05 = 0.049 | |
| I0327 12:46:43.353559 21344 solver.cpp:406] Test net output #5: loss1/accuracy06 = 0.136 |