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2022-11-06 20:36:44,639 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:36:44,639 Model: "SequenceTagger( |
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(embeddings): StackedEmbeddings( |
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(list_embedding_0): FlairEmbeddings( |
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(lm): LanguageModel( |
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(drop): Dropout(p=0.1, inplace=False) |
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(encoder): Embedding(962, 100) |
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(rnn): LSTM(100, 1024) |
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(decoder): Linear(in_features=1024, out_features=962, bias=True) |
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) |
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) |
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(list_embedding_1): FlairEmbeddings( |
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(lm): LanguageModel( |
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(drop): Dropout(p=0.1, inplace=False) |
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(encoder): Embedding(962, 100) |
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(rnn): LSTM(100, 1024) |
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(decoder): Linear(in_features=1024, out_features=962, bias=True) |
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) |
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) |
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) |
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(dropout): Dropout(p=0.005334913013756493, inplace=False) |
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(word_dropout): WordDropout(p=0.05) |
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(locked_dropout): LockedDropout(p=0.5) |
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(embedding2nn): Linear(in_features=2048, out_features=2048, bias=True) |
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(rnn): LSTM(2048, 256, batch_first=True, bidirectional=True) |
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(linear): Linear(in_features=512, out_features=20, bias=True) |
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(loss_function): ViterbiLoss() |
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(crf): CRF() |
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)" |
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2022-11-06 20:36:44,639 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:36:44,639 Corpus: "Corpus: 5496 train + 672 dev + 892 test sentences" |
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2022-11-06 20:36:44,639 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:36:44,640 Parameters: |
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2022-11-06 20:36:44,640 - learning_rate: "0.100000" |
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2022-11-06 20:36:44,640 - mini_batch_size: "16" |
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2022-11-06 20:36:44,640 - patience: "3" |
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2022-11-06 20:36:44,640 - anneal_factor: "0.5" |
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2022-11-06 20:36:44,640 - max_epochs: "150" |
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2022-11-06 20:36:44,640 - shuffle: "True" |
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2022-11-06 20:36:44,640 - train_with_dev: "True" |
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2022-11-06 20:36:44,640 - batch_growth_annealing: "False" |
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2022-11-06 20:36:44,640 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:36:44,640 Model training base path: "pos-tests/uk.flairembeddings.champ" |
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2022-11-06 20:36:44,640 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:36:44,640 Device: cuda:0 |
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2022-11-06 20:36:44,640 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:36:44,641 Embeddings storage mode: cpu |
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2022-11-06 20:36:44,641 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:36:52,658 epoch 1 - iter 38/386 - loss 1.88961718 - samples/sec: 75.87 - lr: 0.100000 |
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2022-11-06 20:36:58,417 epoch 1 - iter 76/386 - loss 1.47768008 - samples/sec: 105.63 - lr: 0.100000 |
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2022-11-06 20:37:05,566 epoch 1 - iter 114/386 - loss 1.19063825 - samples/sec: 85.09 - lr: 0.100000 |
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2022-11-06 20:37:11,577 epoch 1 - iter 152/386 - loss 1.02974511 - samples/sec: 101.19 - lr: 0.100000 |
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2022-11-06 20:37:18,761 epoch 1 - iter 190/386 - loss 0.92486845 - samples/sec: 84.67 - lr: 0.100000 |
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2022-11-06 20:37:27,941 epoch 1 - iter 228/386 - loss 0.81813485 - samples/sec: 66.25 - lr: 0.100000 |
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2022-11-06 20:37:35,445 epoch 1 - iter 266/386 - loss 0.77842545 - samples/sec: 81.05 - lr: 0.100000 |
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2022-11-06 20:37:43,156 epoch 1 - iter 304/386 - loss 0.72645892 - samples/sec: 78.89 - lr: 0.100000 |
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2022-11-06 20:37:51,456 epoch 1 - iter 342/386 - loss 0.68857673 - samples/sec: 73.28 - lr: 0.100000 |
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2022-11-06 20:37:59,557 epoch 1 - iter 380/386 - loss 0.65020291 - samples/sec: 75.08 - lr: 0.100000 |
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2022-11-06 20:38:00,729 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:38:00,729 EPOCH 1 done: loss 0.6450 - lr 0.100000 |
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2022-11-06 20:38:14,564 Evaluating as a multi-label problem: False |
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2022-11-06 20:38:14,679 TEST : loss 0.17086097598075867 - f1-score (micro avg) 0.9512 |
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2022-11-06 20:38:14,794 BAD EPOCHS (no improvement): 0 |
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2022-11-06 20:38:14,951 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:38:20,209 epoch 2 - iter 38/386 - loss 0.35452940 - samples/sec: 115.73 - lr: 0.100000 |
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2022-11-06 20:38:26,172 epoch 2 - iter 76/386 - loss 0.35270834 - samples/sec: 102.02 - lr: 0.100000 |
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2022-11-06 20:38:31,703 epoch 2 - iter 114/386 - loss 0.35270777 - samples/sec: 109.98 - lr: 0.100000 |
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2022-11-06 20:38:37,311 epoch 2 - iter 152/386 - loss 0.34728297 - samples/sec: 108.47 - lr: 0.100000 |
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2022-11-06 20:38:42,764 epoch 2 - iter 190/386 - loss 0.34372065 - samples/sec: 111.57 - lr: 0.100000 |
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2022-11-06 20:38:48,305 epoch 2 - iter 228/386 - loss 0.34270320 - samples/sec: 109.78 - lr: 0.100000 |
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2022-11-06 20:38:54,041 epoch 2 - iter 266/386 - loss 0.33850648 - samples/sec: 106.07 - lr: 0.100000 |
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2022-11-06 20:38:59,745 epoch 2 - iter 304/386 - loss 0.33432568 - samples/sec: 106.65 - lr: 0.100000 |
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2022-11-06 20:39:05,211 epoch 2 - iter 342/386 - loss 0.33065647 - samples/sec: 111.30 - lr: 0.100000 |
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2022-11-06 20:39:10,663 epoch 2 - iter 380/386 - loss 0.32681839 - samples/sec: 111.58 - lr: 0.100000 |
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2022-11-06 20:39:11,364 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:39:11,365 EPOCH 2 done: loss 0.3262 - lr 0.100000 |
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2022-11-06 20:39:20,976 Evaluating as a multi-label problem: False |
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2022-11-06 20:39:21,093 TEST : loss 0.13997453451156616 - f1-score (micro avg) 0.9582 |
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2022-11-06 20:39:21,207 BAD EPOCHS (no improvement): 0 |
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2022-11-06 20:39:21,434 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:39:26,741 epoch 3 - iter 38/386 - loss 0.29294011 - samples/sec: 114.64 - lr: 0.100000 |
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2022-11-06 20:39:31,872 epoch 3 - iter 76/386 - loss 0.29017001 - samples/sec: 118.58 - lr: 0.100000 |
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2022-11-06 20:39:37,423 epoch 3 - iter 114/386 - loss 0.29170149 - samples/sec: 109.59 - lr: 0.100000 |
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2022-11-06 20:39:42,974 epoch 3 - iter 152/386 - loss 0.29094573 - samples/sec: 109.60 - lr: 0.100000 |
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2022-11-06 20:39:48,865 epoch 3 - iter 190/386 - loss 0.28629286 - samples/sec: 103.25 - lr: 0.100000 |
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2022-11-06 20:39:54,264 epoch 3 - iter 228/386 - loss 0.28390933 - samples/sec: 112.68 - lr: 0.100000 |
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2022-11-06 20:39:59,891 epoch 3 - iter 266/386 - loss 0.28294971 - samples/sec: 108.12 - lr: 0.100000 |
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2022-11-06 20:40:05,418 epoch 3 - iter 304/386 - loss 0.28193462 - samples/sec: 110.08 - lr: 0.100000 |
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2022-11-06 20:40:11,108 epoch 3 - iter 342/386 - loss 0.28075670 - samples/sec: 106.91 - lr: 0.100000 |
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2022-11-06 20:40:16,699 epoch 3 - iter 380/386 - loss 0.28035510 - samples/sec: 108.80 - lr: 0.100000 |
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2022-11-06 20:40:17,449 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:40:17,449 EPOCH 3 done: loss 0.2802 - lr 0.100000 |
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2022-11-06 20:40:27,148 Evaluating as a multi-label problem: False |
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2022-11-06 20:40:27,264 TEST : loss 0.12084240466356277 - f1-score (micro avg) 0.9638 |
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2022-11-06 20:40:27,378 BAD EPOCHS (no improvement): 0 |
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2022-11-06 20:40:27,583 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:40:32,829 epoch 4 - iter 38/386 - loss 0.25615401 - samples/sec: 115.99 - lr: 0.100000 |
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2022-11-06 20:40:38,449 epoch 4 - iter 76/386 - loss 0.25978411 - samples/sec: 108.25 - lr: 0.100000 |
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2022-11-06 20:40:43,530 epoch 4 - iter 114/386 - loss 0.25883124 - samples/sec: 119.73 - lr: 0.100000 |
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2022-11-06 20:40:49,225 epoch 4 - iter 152/386 - loss 0.25933191 - samples/sec: 106.82 - lr: 0.100000 |
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2022-11-06 20:40:54,682 epoch 4 - iter 190/386 - loss 0.25994752 - samples/sec: 111.48 - lr: 0.100000 |
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2022-11-06 20:41:00,117 epoch 4 - iter 228/386 - loss 0.25830164 - samples/sec: 111.94 - lr: 0.100000 |
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2022-11-06 20:41:06,007 epoch 4 - iter 266/386 - loss 0.25880376 - samples/sec: 103.27 - lr: 0.100000 |
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2022-11-06 20:41:11,863 epoch 4 - iter 304/386 - loss 0.25683624 - samples/sec: 103.89 - lr: 0.100000 |
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2022-11-06 20:41:17,322 epoch 4 - iter 342/386 - loss 0.25543810 - samples/sec: 111.44 - lr: 0.100000 |
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2022-11-06 20:41:22,801 epoch 4 - iter 380/386 - loss 0.25652313 - samples/sec: 111.03 - lr: 0.100000 |
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2022-11-06 20:41:23,731 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:41:23,732 EPOCH 4 done: loss 0.2567 - lr 0.100000 |
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2022-11-06 20:41:35,645 Evaluating as a multi-label problem: False |
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2022-11-06 20:41:35,761 TEST : loss 0.10487399250268936 - f1-score (micro avg) 0.9673 |
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2022-11-06 20:41:35,875 BAD EPOCHS (no improvement): 0 |
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2022-11-06 20:41:36,092 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:41:41,723 epoch 5 - iter 38/386 - loss 0.22752191 - samples/sec: 108.07 - lr: 0.100000 |
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2022-11-06 20:41:47,194 epoch 5 - iter 76/386 - loss 0.23877064 - samples/sec: 111.20 - lr: 0.100000 |
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2022-11-06 20:41:53,184 epoch 5 - iter 114/386 - loss 0.23723243 - samples/sec: 101.55 - lr: 0.100000 |
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2022-11-06 20:41:58,276 epoch 5 - iter 152/386 - loss 0.23492548 - samples/sec: 120.16 - lr: 0.100000 |
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2022-11-06 20:42:04,003 epoch 5 - iter 190/386 - loss 0.23384590 - samples/sec: 106.22 - lr: 0.100000 |
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2022-11-06 20:42:09,511 epoch 5 - iter 228/386 - loss 0.23679768 - samples/sec: 110.44 - lr: 0.100000 |
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2022-11-06 20:42:15,048 epoch 5 - iter 266/386 - loss 0.23705954 - samples/sec: 109.88 - lr: 0.100000 |
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2022-11-06 20:42:20,836 epoch 5 - iter 304/386 - loss 0.23739395 - samples/sec: 105.09 - lr: 0.100000 |
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2022-11-06 20:42:26,380 epoch 5 - iter 342/386 - loss 0.23844616 - samples/sec: 109.72 - lr: 0.100000 |
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2022-11-06 20:42:31,800 epoch 5 - iter 380/386 - loss 0.23836010 - samples/sec: 112.25 - lr: 0.100000 |
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2022-11-06 20:42:32,565 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:42:32,566 EPOCH 5 done: loss 0.2380 - lr 0.100000 |
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2022-11-06 20:42:42,191 Evaluating as a multi-label problem: False |
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2022-11-06 20:42:42,309 TEST : loss 0.10361631959676743 - f1-score (micro avg) 0.9666 |
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2022-11-06 20:42:42,424 BAD EPOCHS (no improvement): 0 |
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2022-11-06 20:42:42,637 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:42:48,102 epoch 6 - iter 38/386 - loss 0.22899429 - samples/sec: 111.34 - lr: 0.100000 |
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2022-11-06 20:42:53,390 epoch 6 - iter 76/386 - loss 0.22634441 - samples/sec: 115.06 - lr: 0.100000 |
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2022-11-06 20:42:58,802 epoch 6 - iter 114/386 - loss 0.22738383 - samples/sec: 112.40 - lr: 0.100000 |
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2022-11-06 20:43:04,281 epoch 6 - iter 152/386 - loss 0.22831817 - samples/sec: 111.04 - lr: 0.100000 |
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2022-11-06 20:43:09,553 epoch 6 - iter 190/386 - loss 0.22899114 - samples/sec: 115.40 - lr: 0.100000 |
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2022-11-06 20:43:15,176 epoch 6 - iter 228/386 - loss 0.22503611 - samples/sec: 108.19 - lr: 0.100000 |
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2022-11-06 20:43:20,596 epoch 6 - iter 266/386 - loss 0.22562923 - samples/sec: 112.24 - lr: 0.100000 |
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2022-11-06 20:43:26,484 epoch 6 - iter 304/386 - loss 0.22385177 - samples/sec: 103.31 - lr: 0.100000 |
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2022-11-06 20:43:32,694 epoch 6 - iter 342/386 - loss 0.22503902 - samples/sec: 97.96 - lr: 0.100000 |
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2022-11-06 20:43:38,008 epoch 6 - iter 380/386 - loss 0.22506621 - samples/sec: 114.49 - lr: 0.100000 |
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2022-11-06 20:43:38,867 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:43:38,867 EPOCH 6 done: loss 0.2247 - lr 0.100000 |
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2022-11-06 20:43:48,534 Evaluating as a multi-label problem: False |
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2022-11-06 20:43:48,652 TEST : loss 0.10305152833461761 - f1-score (micro avg) 0.9663 |
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2022-11-06 20:43:48,766 BAD EPOCHS (no improvement): 0 |
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2022-11-06 20:43:48,980 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:43:54,333 epoch 7 - iter 38/386 - loss 0.22529638 - samples/sec: 113.68 - lr: 0.100000 |
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2022-11-06 20:44:00,048 epoch 7 - iter 76/386 - loss 0.21567440 - samples/sec: 106.44 - lr: 0.100000 |
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2022-11-06 20:44:05,556 epoch 7 - iter 114/386 - loss 0.22089919 - samples/sec: 110.46 - lr: 0.100000 |
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2022-11-06 20:44:11,230 epoch 7 - iter 152/386 - loss 0.22059846 - samples/sec: 107.20 - lr: 0.100000 |
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2022-11-06 20:44:16,903 epoch 7 - iter 190/386 - loss 0.22095491 - samples/sec: 107.25 - lr: 0.100000 |
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2022-11-06 20:44:22,101 epoch 7 - iter 228/386 - loss 0.21976408 - samples/sec: 117.04 - lr: 0.100000 |
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2022-11-06 20:44:27,485 epoch 7 - iter 266/386 - loss 0.22107223 - samples/sec: 112.99 - lr: 0.100000 |
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2022-11-06 20:44:33,198 epoch 7 - iter 304/386 - loss 0.21947713 - samples/sec: 106.49 - lr: 0.100000 |
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2022-11-06 20:44:38,728 epoch 7 - iter 342/386 - loss 0.21871513 - samples/sec: 110.01 - lr: 0.100000 |
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2022-11-06 20:44:44,565 epoch 7 - iter 380/386 - loss 0.21872143 - samples/sec: 104.22 - lr: 0.100000 |
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2022-11-06 20:44:45,335 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:44:45,336 EPOCH 7 done: loss 0.2184 - lr 0.100000 |
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2022-11-06 20:44:55,019 Evaluating as a multi-label problem: False |
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2022-11-06 20:44:55,137 TEST : loss 0.09460901468992233 - f1-score (micro avg) 0.9693 |
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2022-11-06 20:44:55,250 BAD EPOCHS (no improvement): 0 |
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2022-11-06 20:44:55,463 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:45:01,495 epoch 8 - iter 38/386 - loss 0.21493772 - samples/sec: 100.86 - lr: 0.100000 |
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2022-11-06 20:45:07,230 epoch 8 - iter 76/386 - loss 0.21122181 - samples/sec: 106.09 - lr: 0.100000 |
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2022-11-06 20:45:12,511 epoch 8 - iter 114/386 - loss 0.20912935 - samples/sec: 115.20 - lr: 0.100000 |
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2022-11-06 20:45:18,013 epoch 8 - iter 152/386 - loss 0.20730821 - samples/sec: 110.57 - lr: 0.100000 |
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2022-11-06 20:45:23,128 epoch 8 - iter 190/386 - loss 0.20626902 - samples/sec: 118.92 - lr: 0.100000 |
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2022-11-06 20:45:28,405 epoch 8 - iter 228/386 - loss 0.20860099 - samples/sec: 115.29 - lr: 0.100000 |
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2022-11-06 20:45:33,414 epoch 8 - iter 266/386 - loss 0.20959349 - samples/sec: 121.46 - lr: 0.100000 |
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2022-11-06 20:45:39,424 epoch 8 - iter 304/386 - loss 0.20963436 - samples/sec: 101.22 - lr: 0.100000 |
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2022-11-06 20:45:45,212 epoch 8 - iter 342/386 - loss 0.20919203 - samples/sec: 105.10 - lr: 0.100000 |
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2022-11-06 20:45:50,812 epoch 8 - iter 380/386 - loss 0.20887056 - samples/sec: 108.64 - lr: 0.100000 |
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2022-11-06 20:45:51,741 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:45:51,742 EPOCH 8 done: loss 0.2089 - lr 0.100000 |
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2022-11-06 20:46:01,411 Evaluating as a multi-label problem: False |
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2022-11-06 20:46:01,529 TEST : loss 0.09638751298189163 - f1-score (micro avg) 0.969 |
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2022-11-06 20:46:01,643 BAD EPOCHS (no improvement): 0 |
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2022-11-06 20:46:01,851 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:46:07,202 epoch 9 - iter 38/386 - loss 0.21385281 - samples/sec: 113.71 - lr: 0.100000 |
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2022-11-06 20:46:12,883 epoch 9 - iter 76/386 - loss 0.20570144 - samples/sec: 107.08 - lr: 0.100000 |
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2022-11-06 20:46:18,474 epoch 9 - iter 114/386 - loss 0.19932819 - samples/sec: 108.82 - lr: 0.100000 |
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2022-11-06 20:46:24,012 epoch 9 - iter 152/386 - loss 0.19956175 - samples/sec: 109.85 - lr: 0.100000 |
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2022-11-06 20:46:29,555 epoch 9 - iter 190/386 - loss 0.20140471 - samples/sec: 109.74 - lr: 0.100000 |
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2022-11-06 20:46:35,896 epoch 9 - iter 228/386 - loss 0.20212131 - samples/sec: 95.93 - lr: 0.100000 |
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2022-11-06 20:46:41,010 epoch 9 - iter 266/386 - loss 0.20129877 - samples/sec: 118.97 - lr: 0.100000 |
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2022-11-06 20:46:46,315 epoch 9 - iter 304/386 - loss 0.20214050 - samples/sec: 114.68 - lr: 0.100000 |
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2022-11-06 20:46:51,766 epoch 9 - iter 342/386 - loss 0.20216261 - samples/sec: 111.61 - lr: 0.100000 |
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2022-11-06 20:46:57,274 epoch 9 - iter 380/386 - loss 0.20182060 - samples/sec: 110.45 - lr: 0.100000 |
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2022-11-06 20:46:58,137 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:46:58,137 EPOCH 9 done: loss 0.2015 - lr 0.100000 |
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2022-11-06 20:47:07,877 Evaluating as a multi-label problem: False |
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2022-11-06 20:47:07,993 TEST : loss 0.09079930186271667 - f1-score (micro avg) 0.9707 |
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2022-11-06 20:47:08,107 BAD EPOCHS (no improvement): 0 |
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2022-11-06 20:47:08,312 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:47:14,371 epoch 10 - iter 38/386 - loss 0.18753357 - samples/sec: 100.43 - lr: 0.100000 |
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2022-11-06 20:47:19,847 epoch 10 - iter 76/386 - loss 0.18895331 - samples/sec: 111.09 - lr: 0.100000 |
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2022-11-06 20:47:25,633 epoch 10 - iter 114/386 - loss 0.19191244 - samples/sec: 105.14 - lr: 0.100000 |
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2022-11-06 20:47:31,164 epoch 10 - iter 152/386 - loss 0.19083482 - samples/sec: 109.99 - lr: 0.100000 |
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2022-11-06 20:47:37,079 epoch 10 - iter 190/386 - loss 0.19443441 - samples/sec: 102.84 - lr: 0.100000 |
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2022-11-06 20:47:42,890 epoch 10 - iter 228/386 - loss 0.19279406 - samples/sec: 104.70 - lr: 0.100000 |
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2022-11-06 20:47:48,533 epoch 10 - iter 266/386 - loss 0.19340536 - samples/sec: 107.79 - lr: 0.100000 |
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2022-11-06 20:47:53,622 epoch 10 - iter 304/386 - loss 0.19422661 - samples/sec: 119.56 - lr: 0.100000 |
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2022-11-06 20:47:58,679 epoch 10 - iter 342/386 - loss 0.19472214 - samples/sec: 120.31 - lr: 0.100000 |
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2022-11-06 20:48:04,250 epoch 10 - iter 380/386 - loss 0.19471480 - samples/sec: 109.20 - lr: 0.100000 |
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2022-11-06 20:48:05,211 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:48:05,211 EPOCH 10 done: loss 0.1945 - lr 0.100000 |
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2022-11-06 20:48:14,925 Evaluating as a multi-label problem: False |
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2022-11-06 20:48:15,042 TEST : loss 0.09166789054870605 - f1-score (micro avg) 0.97 |
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2022-11-06 20:48:15,155 BAD EPOCHS (no improvement): 0 |
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2022-11-06 20:48:15,371 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:48:20,625 epoch 11 - iter 38/386 - loss 0.19465953 - samples/sec: 115.82 - lr: 0.100000 |
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2022-11-06 20:48:26,212 epoch 11 - iter 76/386 - loss 0.18636815 - samples/sec: 108.88 - lr: 0.100000 |
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2022-11-06 20:48:31,875 epoch 11 - iter 114/386 - loss 0.18495775 - samples/sec: 107.43 - lr: 0.100000 |
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2022-11-06 20:48:37,842 epoch 11 - iter 152/386 - loss 0.18408789 - samples/sec: 101.94 - lr: 0.100000 |
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2022-11-06 20:48:44,103 epoch 11 - iter 190/386 - loss 0.18540037 - samples/sec: 97.16 - lr: 0.100000 |
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2022-11-06 20:48:49,724 epoch 11 - iter 228/386 - loss 0.18697837 - samples/sec: 108.22 - lr: 0.100000 |
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2022-11-06 20:48:55,206 epoch 11 - iter 266/386 - loss 0.18772444 - samples/sec: 110.97 - lr: 0.100000 |
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2022-11-06 20:49:00,750 epoch 11 - iter 304/386 - loss 0.18780846 - samples/sec: 109.74 - lr: 0.100000 |
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2022-11-06 20:49:05,829 epoch 11 - iter 342/386 - loss 0.18780680 - samples/sec: 119.77 - lr: 0.100000 |
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2022-11-06 20:49:11,200 epoch 11 - iter 380/386 - loss 0.18794317 - samples/sec: 113.29 - lr: 0.100000 |
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2022-11-06 20:49:11,957 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:49:11,957 EPOCH 11 done: loss 0.1881 - lr 0.100000 |
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2022-11-06 20:49:21,692 Evaluating as a multi-label problem: False |
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2022-11-06 20:49:21,810 TEST : loss 0.08823293447494507 - f1-score (micro avg) 0.9713 |
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2022-11-06 20:49:21,925 BAD EPOCHS (no improvement): 0 |
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2022-11-06 20:49:22,138 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:49:27,810 epoch 12 - iter 38/386 - loss 0.19030824 - samples/sec: 107.26 - lr: 0.100000 |
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2022-11-06 20:49:33,408 epoch 12 - iter 76/386 - loss 0.19090830 - samples/sec: 108.69 - lr: 0.100000 |
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2022-11-06 20:49:39,084 epoch 12 - iter 114/386 - loss 0.18845799 - samples/sec: 107.18 - lr: 0.100000 |
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2022-11-06 20:49:44,918 epoch 12 - iter 152/386 - loss 0.18810649 - samples/sec: 104.27 - lr: 0.100000 |
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2022-11-06 20:49:50,979 epoch 12 - iter 190/386 - loss 0.18715379 - samples/sec: 100.38 - lr: 0.100000 |
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2022-11-06 20:49:56,472 epoch 12 - iter 228/386 - loss 0.18446952 - samples/sec: 110.75 - lr: 0.100000 |
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2022-11-06 20:50:01,831 epoch 12 - iter 266/386 - loss 0.18390291 - samples/sec: 113.51 - lr: 0.100000 |
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2022-11-06 20:50:07,542 epoch 12 - iter 304/386 - loss 0.18496511 - samples/sec: 106.53 - lr: 0.100000 |
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2022-11-06 20:50:13,032 epoch 12 - iter 342/386 - loss 0.18602052 - samples/sec: 110.81 - lr: 0.100000 |
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2022-11-06 20:50:18,370 epoch 12 - iter 380/386 - loss 0.18607219 - samples/sec: 113.98 - lr: 0.100000 |
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2022-11-06 20:50:19,126 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:50:19,126 EPOCH 12 done: loss 0.1864 - lr 0.100000 |
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2022-11-06 20:50:28,390 Evaluating as a multi-label problem: False |
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2022-11-06 20:50:28,509 TEST : loss 0.09221376478672028 - f1-score (micro avg) 0.9697 |
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2022-11-06 20:50:28,623 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 20:50:28,837 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:50:34,166 epoch 13 - iter 38/386 - loss 0.18837518 - samples/sec: 114.18 - lr: 0.100000 |
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2022-11-06 20:50:39,865 epoch 13 - iter 76/386 - loss 0.18305753 - samples/sec: 106.86 - lr: 0.100000 |
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2022-11-06 20:50:45,311 epoch 13 - iter 114/386 - loss 0.17754302 - samples/sec: 111.72 - lr: 0.100000 |
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2022-11-06 20:50:50,952 epoch 13 - iter 152/386 - loss 0.17535643 - samples/sec: 107.84 - lr: 0.100000 |
|
2022-11-06 20:50:56,810 epoch 13 - iter 190/386 - loss 0.17662633 - samples/sec: 103.85 - lr: 0.100000 |
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2022-11-06 20:51:02,296 epoch 13 - iter 228/386 - loss 0.17879492 - samples/sec: 110.88 - lr: 0.100000 |
|
2022-11-06 20:51:08,204 epoch 13 - iter 266/386 - loss 0.17749818 - samples/sec: 102.98 - lr: 0.100000 |
|
2022-11-06 20:51:13,932 epoch 13 - iter 304/386 - loss 0.17909369 - samples/sec: 106.20 - lr: 0.100000 |
|
2022-11-06 20:51:19,654 epoch 13 - iter 342/386 - loss 0.17936686 - samples/sec: 106.33 - lr: 0.100000 |
|
2022-11-06 20:51:25,470 epoch 13 - iter 380/386 - loss 0.17907693 - samples/sec: 104.60 - lr: 0.100000 |
|
2022-11-06 20:51:26,408 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:51:26,409 EPOCH 13 done: loss 0.1789 - lr 0.100000 |
|
2022-11-06 20:51:35,303 Evaluating as a multi-label problem: False |
|
2022-11-06 20:51:35,420 TEST : loss 0.08666753023862839 - f1-score (micro avg) 0.9711 |
|
2022-11-06 20:51:35,535 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 20:51:35,751 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 20:51:41,328 epoch 14 - iter 38/386 - loss 0.17659370 - samples/sec: 109.11 - lr: 0.100000 |
|
2022-11-06 20:51:46,724 epoch 14 - iter 76/386 - loss 0.17717785 - samples/sec: 112.74 - lr: 0.100000 |
|
2022-11-06 20:51:52,363 epoch 14 - iter 114/386 - loss 0.17727583 - samples/sec: 107.88 - lr: 0.100000 |
|
2022-11-06 20:51:57,835 epoch 14 - iter 152/386 - loss 0.17558755 - samples/sec: 111.18 - lr: 0.100000 |
|
2022-11-06 20:52:03,438 epoch 14 - iter 190/386 - loss 0.17647551 - samples/sec: 108.57 - lr: 0.100000 |
|
2022-11-06 20:52:09,148 epoch 14 - iter 228/386 - loss 0.17614281 - samples/sec: 106.54 - lr: 0.100000 |
|
2022-11-06 20:52:14,747 epoch 14 - iter 266/386 - loss 0.17762340 - samples/sec: 108.66 - lr: 0.100000 |
|
2022-11-06 20:52:20,348 epoch 14 - iter 304/386 - loss 0.17659061 - samples/sec: 108.60 - lr: 0.100000 |
|
2022-11-06 20:52:26,079 epoch 14 - iter 342/386 - loss 0.17538245 - samples/sec: 106.17 - lr: 0.100000 |
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2022-11-06 20:52:31,932 epoch 14 - iter 380/386 - loss 0.17530091 - samples/sec: 103.93 - lr: 0.100000 |
|
2022-11-06 20:52:32,726 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 20:52:32,727 EPOCH 14 done: loss 0.1751 - lr 0.100000 |
|
2022-11-06 20:52:42,073 Evaluating as a multi-label problem: False |
|
2022-11-06 20:52:42,190 TEST : loss 0.08278612792491913 - f1-score (micro avg) 0.9732 |
|
2022-11-06 20:52:42,302 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 20:52:42,515 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 20:52:47,798 epoch 15 - iter 38/386 - loss 0.16309852 - samples/sec: 115.19 - lr: 0.100000 |
|
2022-11-06 20:52:53,422 epoch 15 - iter 76/386 - loss 0.16417836 - samples/sec: 108.17 - lr: 0.100000 |
|
2022-11-06 20:52:59,582 epoch 15 - iter 114/386 - loss 0.16900543 - samples/sec: 98.75 - lr: 0.100000 |
|
2022-11-06 20:53:04,615 epoch 15 - iter 152/386 - loss 0.16798509 - samples/sec: 120.89 - lr: 0.100000 |
|
2022-11-06 20:53:10,430 epoch 15 - iter 190/386 - loss 0.17086367 - samples/sec: 104.61 - lr: 0.100000 |
|
2022-11-06 20:53:16,529 epoch 15 - iter 228/386 - loss 0.16985321 - samples/sec: 99.75 - lr: 0.100000 |
|
2022-11-06 20:53:21,908 epoch 15 - iter 266/386 - loss 0.17032852 - samples/sec: 113.10 - lr: 0.100000 |
|
2022-11-06 20:53:27,343 epoch 15 - iter 304/386 - loss 0.17092036 - samples/sec: 111.92 - lr: 0.100000 |
|
2022-11-06 20:53:33,186 epoch 15 - iter 342/386 - loss 0.17242412 - samples/sec: 104.12 - lr: 0.100000 |
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2022-11-06 20:53:38,393 epoch 15 - iter 380/386 - loss 0.17357857 - samples/sec: 116.85 - lr: 0.100000 |
|
2022-11-06 20:53:39,106 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 20:53:39,107 EPOCH 15 done: loss 0.1732 - lr 0.100000 |
|
2022-11-06 20:53:51,076 Evaluating as a multi-label problem: False |
|
2022-11-06 20:53:51,192 TEST : loss 0.08690010011196136 - f1-score (micro avg) 0.972 |
|
2022-11-06 20:53:51,306 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 20:53:51,510 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 20:53:56,589 epoch 16 - iter 38/386 - loss 0.17036775 - samples/sec: 119.81 - lr: 0.100000 |
|
2022-11-06 20:54:02,420 epoch 16 - iter 76/386 - loss 0.16920502 - samples/sec: 104.34 - lr: 0.100000 |
|
2022-11-06 20:54:07,695 epoch 16 - iter 114/386 - loss 0.16618744 - samples/sec: 115.32 - lr: 0.100000 |
|
2022-11-06 20:54:13,031 epoch 16 - iter 152/386 - loss 0.16660212 - samples/sec: 114.03 - lr: 0.100000 |
|
2022-11-06 20:54:18,443 epoch 16 - iter 190/386 - loss 0.16844597 - samples/sec: 112.40 - lr: 0.100000 |
|
2022-11-06 20:54:23,874 epoch 16 - iter 228/386 - loss 0.16658228 - samples/sec: 112.01 - lr: 0.100000 |
|
2022-11-06 20:54:29,566 epoch 16 - iter 266/386 - loss 0.16713623 - samples/sec: 106.89 - lr: 0.100000 |
|
2022-11-06 20:54:35,356 epoch 16 - iter 304/386 - loss 0.16775392 - samples/sec: 105.07 - lr: 0.100000 |
|
2022-11-06 20:54:40,973 epoch 16 - iter 342/386 - loss 0.16753092 - samples/sec: 108.31 - lr: 0.100000 |
|
2022-11-06 20:54:47,190 epoch 16 - iter 380/386 - loss 0.16711554 - samples/sec: 97.84 - lr: 0.100000 |
|
2022-11-06 20:54:48,047 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 20:54:48,047 EPOCH 16 done: loss 0.1675 - lr 0.100000 |
|
2022-11-06 20:54:57,695 Evaluating as a multi-label problem: False |
|
2022-11-06 20:54:57,813 TEST : loss 0.08330953121185303 - f1-score (micro avg) 0.9734 |
|
2022-11-06 20:54:57,930 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 20:54:58,141 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 20:55:03,292 epoch 17 - iter 38/386 - loss 0.17502829 - samples/sec: 118.14 - lr: 0.100000 |
|
2022-11-06 20:55:08,797 epoch 17 - iter 76/386 - loss 0.16843116 - samples/sec: 110.51 - lr: 0.100000 |
|
2022-11-06 20:55:13,948 epoch 17 - iter 114/386 - loss 0.16803005 - samples/sec: 118.11 - lr: 0.100000 |
|
2022-11-06 20:55:19,380 epoch 17 - iter 152/386 - loss 0.16644258 - samples/sec: 111.98 - lr: 0.100000 |
|
2022-11-06 20:55:25,262 epoch 17 - iter 190/386 - loss 0.16591449 - samples/sec: 103.42 - lr: 0.100000 |
|
2022-11-06 20:55:31,113 epoch 17 - iter 228/386 - loss 0.16655165 - samples/sec: 103.97 - lr: 0.100000 |
|
2022-11-06 20:55:36,772 epoch 17 - iter 266/386 - loss 0.16720170 - samples/sec: 107.52 - lr: 0.100000 |
|
2022-11-06 20:55:42,603 epoch 17 - iter 304/386 - loss 0.16818979 - samples/sec: 104.32 - lr: 0.100000 |
|
2022-11-06 20:55:48,158 epoch 17 - iter 342/386 - loss 0.16742200 - samples/sec: 109.51 - lr: 0.100000 |
|
2022-11-06 20:55:53,675 epoch 17 - iter 380/386 - loss 0.16757147 - samples/sec: 110.28 - lr: 0.100000 |
|
2022-11-06 20:55:54,502 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:55:54,503 EPOCH 17 done: loss 0.1678 - lr 0.100000 |
|
2022-11-06 20:56:04,246 Evaluating as a multi-label problem: False |
|
2022-11-06 20:56:04,363 TEST : loss 0.08121314644813538 - f1-score (micro avg) 0.9744 |
|
2022-11-06 20:56:04,477 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 20:56:04,688 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 20:56:09,972 epoch 18 - iter 38/386 - loss 0.16529975 - samples/sec: 115.16 - lr: 0.100000 |
|
2022-11-06 20:56:15,051 epoch 18 - iter 76/386 - loss 0.16989333 - samples/sec: 119.80 - lr: 0.100000 |
|
2022-11-06 20:56:20,209 epoch 18 - iter 114/386 - loss 0.16695045 - samples/sec: 117.94 - lr: 0.100000 |
|
2022-11-06 20:56:26,104 epoch 18 - iter 152/386 - loss 0.16782753 - samples/sec: 103.19 - lr: 0.100000 |
|
2022-11-06 20:56:31,985 epoch 18 - iter 190/386 - loss 0.16581193 - samples/sec: 103.44 - lr: 0.100000 |
|
2022-11-06 20:56:37,824 epoch 18 - iter 228/386 - loss 0.16465238 - samples/sec: 104.19 - lr: 0.100000 |
|
2022-11-06 20:56:43,581 epoch 18 - iter 266/386 - loss 0.16401545 - samples/sec: 105.68 - lr: 0.100000 |
|
2022-11-06 20:56:49,303 epoch 18 - iter 304/386 - loss 0.16283744 - samples/sec: 106.32 - lr: 0.100000 |
|
2022-11-06 20:56:54,990 epoch 18 - iter 342/386 - loss 0.16172837 - samples/sec: 106.96 - lr: 0.100000 |
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2022-11-06 20:57:00,441 epoch 18 - iter 380/386 - loss 0.16220310 - samples/sec: 111.62 - lr: 0.100000 |
|
2022-11-06 20:57:01,181 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 20:57:01,182 EPOCH 18 done: loss 0.1623 - lr 0.100000 |
|
2022-11-06 20:57:10,902 Evaluating as a multi-label problem: False |
|
2022-11-06 20:57:11,019 TEST : loss 0.07836408168077469 - f1-score (micro avg) 0.9745 |
|
2022-11-06 20:57:11,133 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 20:57:11,347 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 20:57:17,197 epoch 19 - iter 38/386 - loss 0.16558504 - samples/sec: 104.03 - lr: 0.100000 |
|
2022-11-06 20:57:22,661 epoch 19 - iter 76/386 - loss 0.16480656 - samples/sec: 111.34 - lr: 0.100000 |
|
2022-11-06 20:57:28,015 epoch 19 - iter 114/386 - loss 0.16165750 - samples/sec: 113.62 - lr: 0.100000 |
|
2022-11-06 20:57:33,088 epoch 19 - iter 152/386 - loss 0.16171112 - samples/sec: 119.94 - lr: 0.100000 |
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2022-11-06 20:57:38,973 epoch 19 - iter 190/386 - loss 0.16295973 - samples/sec: 103.36 - lr: 0.100000 |
|
2022-11-06 20:57:44,532 epoch 19 - iter 228/386 - loss 0.16345664 - samples/sec: 109.43 - lr: 0.100000 |
|
2022-11-06 20:57:50,631 epoch 19 - iter 266/386 - loss 0.16293156 - samples/sec: 99.74 - lr: 0.100000 |
|
2022-11-06 20:57:56,147 epoch 19 - iter 304/386 - loss 0.16175446 - samples/sec: 110.30 - lr: 0.100000 |
|
2022-11-06 20:58:02,000 epoch 19 - iter 342/386 - loss 0.16181308 - samples/sec: 103.93 - lr: 0.100000 |
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2022-11-06 20:58:07,419 epoch 19 - iter 380/386 - loss 0.16159155 - samples/sec: 112.28 - lr: 0.100000 |
|
2022-11-06 20:58:08,189 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:58:08,189 EPOCH 19 done: loss 0.1617 - lr 0.100000 |
|
2022-11-06 20:58:17,915 Evaluating as a multi-label problem: False |
|
2022-11-06 20:58:18,032 TEST : loss 0.08216149359941483 - f1-score (micro avg) 0.9747 |
|
2022-11-06 20:58:18,146 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 20:58:18,357 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 20:58:24,010 epoch 20 - iter 38/386 - loss 0.15493718 - samples/sec: 107.64 - lr: 0.100000 |
|
2022-11-06 20:58:29,441 epoch 20 - iter 76/386 - loss 0.15938559 - samples/sec: 112.01 - lr: 0.100000 |
|
2022-11-06 20:58:35,738 epoch 20 - iter 114/386 - loss 0.16028978 - samples/sec: 96.61 - lr: 0.100000 |
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2022-11-06 20:58:41,385 epoch 20 - iter 152/386 - loss 0.15622031 - samples/sec: 107.72 - lr: 0.100000 |
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2022-11-06 20:58:46,596 epoch 20 - iter 190/386 - loss 0.15824790 - samples/sec: 116.77 - lr: 0.100000 |
|
2022-11-06 20:58:51,920 epoch 20 - iter 228/386 - loss 0.15992430 - samples/sec: 114.27 - lr: 0.100000 |
|
2022-11-06 20:58:57,417 epoch 20 - iter 266/386 - loss 0.16045659 - samples/sec: 110.66 - lr: 0.100000 |
|
2022-11-06 20:59:02,733 epoch 20 - iter 304/386 - loss 0.15924395 - samples/sec: 114.45 - lr: 0.100000 |
|
2022-11-06 20:59:08,115 epoch 20 - iter 342/386 - loss 0.15996715 - samples/sec: 113.03 - lr: 0.100000 |
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2022-11-06 20:59:14,095 epoch 20 - iter 380/386 - loss 0.15988839 - samples/sec: 101.72 - lr: 0.100000 |
|
2022-11-06 20:59:14,920 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 20:59:14,920 EPOCH 20 done: loss 0.1600 - lr 0.100000 |
|
2022-11-06 20:59:24,629 Evaluating as a multi-label problem: False |
|
2022-11-06 20:59:24,747 TEST : loss 0.08073458075523376 - f1-score (micro avg) 0.9737 |
|
2022-11-06 20:59:24,861 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 20:59:25,069 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 20:59:30,496 epoch 21 - iter 38/386 - loss 0.15646384 - samples/sec: 112.12 - lr: 0.100000 |
|
2022-11-06 20:59:36,689 epoch 21 - iter 76/386 - loss 0.15833186 - samples/sec: 98.22 - lr: 0.100000 |
|
2022-11-06 20:59:42,302 epoch 21 - iter 114/386 - loss 0.15639674 - samples/sec: 108.39 - lr: 0.100000 |
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2022-11-06 20:59:47,388 epoch 21 - iter 152/386 - loss 0.15523675 - samples/sec: 119.62 - lr: 0.100000 |
|
2022-11-06 20:59:52,743 epoch 21 - iter 190/386 - loss 0.15815249 - samples/sec: 113.59 - lr: 0.100000 |
|
2022-11-06 20:59:57,973 epoch 21 - iter 228/386 - loss 0.15968102 - samples/sec: 116.33 - lr: 0.100000 |
|
2022-11-06 21:00:03,286 epoch 21 - iter 266/386 - loss 0.15926273 - samples/sec: 114.49 - lr: 0.100000 |
|
2022-11-06 21:00:08,837 epoch 21 - iter 304/386 - loss 0.15918787 - samples/sec: 109.61 - lr: 0.100000 |
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2022-11-06 21:00:14,457 epoch 21 - iter 342/386 - loss 0.15886766 - samples/sec: 108.23 - lr: 0.100000 |
|
2022-11-06 21:00:20,472 epoch 21 - iter 380/386 - loss 0.15755869 - samples/sec: 101.14 - lr: 0.100000 |
|
2022-11-06 21:00:21,352 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:00:21,352 EPOCH 21 done: loss 0.1575 - lr 0.100000 |
|
2022-11-06 21:00:31,068 Evaluating as a multi-label problem: False |
|
2022-11-06 21:00:31,185 TEST : loss 0.08205189555883408 - f1-score (micro avg) 0.9743 |
|
2022-11-06 21:00:31,301 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:00:31,505 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:00:37,354 epoch 22 - iter 38/386 - loss 0.15864763 - samples/sec: 104.03 - lr: 0.100000 |
|
2022-11-06 21:00:43,136 epoch 22 - iter 76/386 - loss 0.15493977 - samples/sec: 105.21 - lr: 0.100000 |
|
2022-11-06 21:00:48,831 epoch 22 - iter 114/386 - loss 0.15076336 - samples/sec: 106.82 - lr: 0.100000 |
|
2022-11-06 21:00:54,557 epoch 22 - iter 152/386 - loss 0.15246751 - samples/sec: 106.24 - lr: 0.100000 |
|
2022-11-06 21:01:00,455 epoch 22 - iter 190/386 - loss 0.15165248 - samples/sec: 103.15 - lr: 0.100000 |
|
2022-11-06 21:01:05,621 epoch 22 - iter 228/386 - loss 0.15177154 - samples/sec: 117.75 - lr: 0.100000 |
|
2022-11-06 21:01:10,922 epoch 22 - iter 266/386 - loss 0.15051751 - samples/sec: 114.76 - lr: 0.100000 |
|
2022-11-06 21:01:16,760 epoch 22 - iter 304/386 - loss 0.15118076 - samples/sec: 104.21 - lr: 0.100000 |
|
2022-11-06 21:01:22,266 epoch 22 - iter 342/386 - loss 0.15055201 - samples/sec: 110.50 - lr: 0.100000 |
|
2022-11-06 21:01:27,611 epoch 22 - iter 380/386 - loss 0.15119519 - samples/sec: 113.82 - lr: 0.100000 |
|
2022-11-06 21:01:28,340 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:01:28,340 EPOCH 22 done: loss 0.1515 - lr 0.100000 |
|
2022-11-06 21:01:38,050 Evaluating as a multi-label problem: False |
|
2022-11-06 21:01:38,168 TEST : loss 0.07914499193429947 - f1-score (micro avg) 0.9744 |
|
2022-11-06 21:01:38,282 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:01:38,489 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:01:44,087 epoch 23 - iter 38/386 - loss 0.13755212 - samples/sec: 108.70 - lr: 0.100000 |
|
2022-11-06 21:01:49,886 epoch 23 - iter 76/386 - loss 0.14831372 - samples/sec: 104.90 - lr: 0.100000 |
|
2022-11-06 21:01:55,850 epoch 23 - iter 114/386 - loss 0.15013172 - samples/sec: 102.00 - lr: 0.100000 |
|
2022-11-06 21:02:01,257 epoch 23 - iter 152/386 - loss 0.15083360 - samples/sec: 112.52 - lr: 0.100000 |
|
2022-11-06 21:02:06,555 epoch 23 - iter 190/386 - loss 0.15422736 - samples/sec: 114.84 - lr: 0.100000 |
|
2022-11-06 21:02:11,963 epoch 23 - iter 228/386 - loss 0.15444813 - samples/sec: 112.47 - lr: 0.100000 |
|
2022-11-06 21:02:17,169 epoch 23 - iter 266/386 - loss 0.15525693 - samples/sec: 116.88 - lr: 0.100000 |
|
2022-11-06 21:02:22,061 epoch 23 - iter 304/386 - loss 0.15494546 - samples/sec: 124.37 - lr: 0.100000 |
|
2022-11-06 21:02:27,705 epoch 23 - iter 342/386 - loss 0.15405838 - samples/sec: 107.79 - lr: 0.100000 |
|
2022-11-06 21:02:33,764 epoch 23 - iter 380/386 - loss 0.15553576 - samples/sec: 100.39 - lr: 0.100000 |
|
2022-11-06 21:02:34,599 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:02:34,599 EPOCH 23 done: loss 0.1554 - lr 0.100000 |
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2022-11-06 21:02:44,235 Evaluating as a multi-label problem: False |
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2022-11-06 21:02:44,352 TEST : loss 0.07991506159305573 - f1-score (micro avg) 0.9745 |
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2022-11-06 21:02:44,466 BAD EPOCHS (no improvement): 1 |
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2022-11-06 21:02:44,683 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:02:50,503 epoch 24 - iter 38/386 - loss 0.14697074 - samples/sec: 104.54 - lr: 0.100000 |
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2022-11-06 21:02:56,444 epoch 24 - iter 76/386 - loss 0.15070964 - samples/sec: 102.39 - lr: 0.100000 |
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2022-11-06 21:03:01,829 epoch 24 - iter 114/386 - loss 0.14717350 - samples/sec: 112.97 - lr: 0.100000 |
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2022-11-06 21:03:07,250 epoch 24 - iter 152/386 - loss 0.14756800 - samples/sec: 112.23 - lr: 0.100000 |
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2022-11-06 21:03:12,903 epoch 24 - iter 190/386 - loss 0.14806885 - samples/sec: 107.63 - lr: 0.100000 |
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2022-11-06 21:03:18,413 epoch 24 - iter 228/386 - loss 0.14679408 - samples/sec: 110.39 - lr: 0.100000 |
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2022-11-06 21:03:24,214 epoch 24 - iter 266/386 - loss 0.14714592 - samples/sec: 104.87 - lr: 0.100000 |
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2022-11-06 21:03:29,178 epoch 24 - iter 304/386 - loss 0.14747206 - samples/sec: 122.56 - lr: 0.100000 |
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2022-11-06 21:03:34,142 epoch 24 - iter 342/386 - loss 0.14818296 - samples/sec: 122.56 - lr: 0.100000 |
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2022-11-06 21:03:39,739 epoch 24 - iter 380/386 - loss 0.14974964 - samples/sec: 108.71 - lr: 0.100000 |
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2022-11-06 21:03:40,537 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:03:40,537 EPOCH 24 done: loss 0.1506 - lr 0.100000 |
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2022-11-06 21:03:50,243 Evaluating as a multi-label problem: False |
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2022-11-06 21:03:50,360 TEST : loss 0.07870050519704819 - f1-score (micro avg) 0.9741 |
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2022-11-06 21:03:50,475 BAD EPOCHS (no improvement): 0 |
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2022-11-06 21:03:50,687 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:03:56,233 epoch 25 - iter 38/386 - loss 0.13940087 - samples/sec: 109.72 - lr: 0.100000 |
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2022-11-06 21:04:01,975 epoch 25 - iter 76/386 - loss 0.14896394 - samples/sec: 105.96 - lr: 0.100000 |
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2022-11-06 21:04:07,889 epoch 25 - iter 114/386 - loss 0.14707969 - samples/sec: 102.85 - lr: 0.100000 |
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2022-11-06 21:04:13,194 epoch 25 - iter 152/386 - loss 0.14597872 - samples/sec: 114.69 - lr: 0.100000 |
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2022-11-06 21:04:18,624 epoch 25 - iter 190/386 - loss 0.14539814 - samples/sec: 112.04 - lr: 0.100000 |
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2022-11-06 21:04:23,930 epoch 25 - iter 228/386 - loss 0.14700191 - samples/sec: 114.64 - lr: 0.100000 |
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2022-11-06 21:04:29,612 epoch 25 - iter 266/386 - loss 0.14515688 - samples/sec: 107.08 - lr: 0.100000 |
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2022-11-06 21:04:35,184 epoch 25 - iter 304/386 - loss 0.14791253 - samples/sec: 109.17 - lr: 0.100000 |
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2022-11-06 21:04:40,665 epoch 25 - iter 342/386 - loss 0.14734839 - samples/sec: 111.00 - lr: 0.100000 |
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2022-11-06 21:04:45,848 epoch 25 - iter 380/386 - loss 0.14822894 - samples/sec: 117.40 - lr: 0.100000 |
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2022-11-06 21:04:46,703 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:04:46,703 EPOCH 25 done: loss 0.1481 - lr 0.100000 |
|
2022-11-06 21:04:58,721 Evaluating as a multi-label problem: False |
|
2022-11-06 21:04:58,838 TEST : loss 0.07901712507009506 - f1-score (micro avg) 0.9746 |
|
2022-11-06 21:04:58,952 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:04:59,165 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:05:04,673 epoch 26 - iter 38/386 - loss 0.14282227 - samples/sec: 110.46 - lr: 0.100000 |
|
2022-11-06 21:05:10,143 epoch 26 - iter 76/386 - loss 0.14009603 - samples/sec: 111.22 - lr: 0.100000 |
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2022-11-06 21:05:15,479 epoch 26 - iter 114/386 - loss 0.14511417 - samples/sec: 114.01 - lr: 0.100000 |
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2022-11-06 21:05:20,755 epoch 26 - iter 152/386 - loss 0.14774136 - samples/sec: 115.31 - lr: 0.100000 |
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2022-11-06 21:05:26,550 epoch 26 - iter 190/386 - loss 0.14833681 - samples/sec: 104.98 - lr: 0.100000 |
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2022-11-06 21:05:32,041 epoch 26 - iter 228/386 - loss 0.14767418 - samples/sec: 110.80 - lr: 0.100000 |
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2022-11-06 21:05:37,997 epoch 26 - iter 266/386 - loss 0.14808159 - samples/sec: 102.14 - lr: 0.100000 |
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2022-11-06 21:05:43,704 epoch 26 - iter 304/386 - loss 0.14801024 - samples/sec: 106.59 - lr: 0.100000 |
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2022-11-06 21:05:49,439 epoch 26 - iter 342/386 - loss 0.14801693 - samples/sec: 106.06 - lr: 0.100000 |
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2022-11-06 21:05:55,135 epoch 26 - iter 380/386 - loss 0.14740170 - samples/sec: 106.80 - lr: 0.100000 |
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2022-11-06 21:05:55,861 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:05:55,861 EPOCH 26 done: loss 0.1475 - lr 0.100000 |
|
2022-11-06 21:06:05,533 Evaluating as a multi-label problem: False |
|
2022-11-06 21:06:05,651 TEST : loss 0.07874496281147003 - f1-score (micro avg) 0.9749 |
|
2022-11-06 21:06:05,766 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:06:05,968 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:06:11,873 epoch 27 - iter 38/386 - loss 0.13004283 - samples/sec: 103.03 - lr: 0.100000 |
|
2022-11-06 21:06:17,429 epoch 27 - iter 76/386 - loss 0.13711483 - samples/sec: 109.50 - lr: 0.100000 |
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2022-11-06 21:06:22,939 epoch 27 - iter 114/386 - loss 0.13564053 - samples/sec: 110.41 - lr: 0.100000 |
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2022-11-06 21:06:28,139 epoch 27 - iter 152/386 - loss 0.13669751 - samples/sec: 116.98 - lr: 0.100000 |
|
2022-11-06 21:06:34,190 epoch 27 - iter 190/386 - loss 0.13980698 - samples/sec: 100.54 - lr: 0.100000 |
|
2022-11-06 21:06:39,906 epoch 27 - iter 228/386 - loss 0.14014600 - samples/sec: 106.43 - lr: 0.100000 |
|
2022-11-06 21:06:45,374 epoch 27 - iter 266/386 - loss 0.14190313 - samples/sec: 111.25 - lr: 0.100000 |
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2022-11-06 21:06:50,848 epoch 27 - iter 304/386 - loss 0.14403091 - samples/sec: 111.12 - lr: 0.100000 |
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2022-11-06 21:06:56,487 epoch 27 - iter 342/386 - loss 0.14531144 - samples/sec: 107.89 - lr: 0.100000 |
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2022-11-06 21:07:02,016 epoch 27 - iter 380/386 - loss 0.14536325 - samples/sec: 110.03 - lr: 0.100000 |
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2022-11-06 21:07:02,857 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:07:02,858 EPOCH 27 done: loss 0.1455 - lr 0.100000 |
|
2022-11-06 21:07:11,706 Evaluating as a multi-label problem: False |
|
2022-11-06 21:07:11,820 TEST : loss 0.07635033130645752 - f1-score (micro avg) 0.9757 |
|
2022-11-06 21:07:11,932 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:07:12,133 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:07:17,911 epoch 28 - iter 38/386 - loss 0.13194440 - samples/sec: 105.31 - lr: 0.100000 |
|
2022-11-06 21:07:23,934 epoch 28 - iter 76/386 - loss 0.13987553 - samples/sec: 101.00 - lr: 0.100000 |
|
2022-11-06 21:07:29,141 epoch 28 - iter 114/386 - loss 0.13984912 - samples/sec: 116.84 - lr: 0.100000 |
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2022-11-06 21:07:34,786 epoch 28 - iter 152/386 - loss 0.14119805 - samples/sec: 107.76 - lr: 0.100000 |
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2022-11-06 21:07:40,664 epoch 28 - iter 190/386 - loss 0.14009221 - samples/sec: 103.49 - lr: 0.100000 |
|
2022-11-06 21:07:46,086 epoch 28 - iter 228/386 - loss 0.14194481 - samples/sec: 112.19 - lr: 0.100000 |
|
2022-11-06 21:07:51,402 epoch 28 - iter 266/386 - loss 0.14287215 - samples/sec: 114.43 - lr: 0.100000 |
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2022-11-06 21:07:56,794 epoch 28 - iter 304/386 - loss 0.14232579 - samples/sec: 112.83 - lr: 0.100000 |
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2022-11-06 21:08:02,371 epoch 28 - iter 342/386 - loss 0.14283220 - samples/sec: 109.07 - lr: 0.100000 |
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2022-11-06 21:08:07,977 epoch 28 - iter 380/386 - loss 0.14188657 - samples/sec: 108.51 - lr: 0.100000 |
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2022-11-06 21:08:08,829 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:08:08,829 EPOCH 28 done: loss 0.1414 - lr 0.100000 |
|
2022-11-06 21:08:17,807 Evaluating as a multi-label problem: False |
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2022-11-06 21:08:17,921 TEST : loss 0.07446986436843872 - f1-score (micro avg) 0.9765 |
|
2022-11-06 21:08:18,033 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:08:18,240 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:08:23,510 epoch 29 - iter 38/386 - loss 0.14492015 - samples/sec: 115.46 - lr: 0.100000 |
|
2022-11-06 21:08:29,410 epoch 29 - iter 76/386 - loss 0.14047206 - samples/sec: 103.11 - lr: 0.100000 |
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2022-11-06 21:08:34,873 epoch 29 - iter 114/386 - loss 0.13804250 - samples/sec: 111.34 - lr: 0.100000 |
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2022-11-06 21:08:40,671 epoch 29 - iter 152/386 - loss 0.13884114 - samples/sec: 104.92 - lr: 0.100000 |
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2022-11-06 21:08:45,997 epoch 29 - iter 190/386 - loss 0.13904629 - samples/sec: 114.23 - lr: 0.100000 |
|
2022-11-06 21:08:51,833 epoch 29 - iter 228/386 - loss 0.13886545 - samples/sec: 104.22 - lr: 0.100000 |
|
2022-11-06 21:08:57,787 epoch 29 - iter 266/386 - loss 0.14075134 - samples/sec: 102.17 - lr: 0.100000 |
|
2022-11-06 21:09:03,106 epoch 29 - iter 304/386 - loss 0.14174863 - samples/sec: 114.37 - lr: 0.100000 |
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2022-11-06 21:09:08,622 epoch 29 - iter 342/386 - loss 0.14258607 - samples/sec: 110.29 - lr: 0.100000 |
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2022-11-06 21:09:14,442 epoch 29 - iter 380/386 - loss 0.14217338 - samples/sec: 104.52 - lr: 0.100000 |
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2022-11-06 21:09:15,384 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:09:15,385 EPOCH 29 done: loss 0.1419 - lr 0.100000 |
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2022-11-06 21:09:24,917 Evaluating as a multi-label problem: False |
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2022-11-06 21:09:25,031 TEST : loss 0.07629775255918503 - f1-score (micro avg) 0.977 |
|
2022-11-06 21:09:25,143 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 21:09:25,353 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:09:30,737 epoch 30 - iter 38/386 - loss 0.13435244 - samples/sec: 113.02 - lr: 0.100000 |
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2022-11-06 21:09:36,689 epoch 30 - iter 76/386 - loss 0.13767440 - samples/sec: 102.20 - lr: 0.100000 |
|
2022-11-06 21:09:42,013 epoch 30 - iter 114/386 - loss 0.13696206 - samples/sec: 114.27 - lr: 0.100000 |
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2022-11-06 21:09:47,791 epoch 30 - iter 152/386 - loss 0.13829190 - samples/sec: 105.27 - lr: 0.100000 |
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2022-11-06 21:09:53,579 epoch 30 - iter 190/386 - loss 0.13687404 - samples/sec: 105.11 - lr: 0.100000 |
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2022-11-06 21:09:58,847 epoch 30 - iter 228/386 - loss 0.13774599 - samples/sec: 115.47 - lr: 0.100000 |
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2022-11-06 21:10:04,568 epoch 30 - iter 266/386 - loss 0.13901783 - samples/sec: 107.13 - lr: 0.100000 |
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2022-11-06 21:10:10,503 epoch 30 - iter 304/386 - loss 0.13908626 - samples/sec: 102.49 - lr: 0.100000 |
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2022-11-06 21:10:16,164 epoch 30 - iter 342/386 - loss 0.14021005 - samples/sec: 107.47 - lr: 0.100000 |
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2022-11-06 21:10:21,615 epoch 30 - iter 380/386 - loss 0.14053641 - samples/sec: 111.59 - lr: 0.100000 |
|
2022-11-06 21:10:22,475 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:10:22,475 EPOCH 30 done: loss 0.1405 - lr 0.100000 |
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2022-11-06 21:10:32,025 Evaluating as a multi-label problem: False |
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2022-11-06 21:10:32,139 TEST : loss 0.08012723922729492 - f1-score (micro avg) 0.9751 |
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2022-11-06 21:10:32,251 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:10:32,460 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:10:37,874 epoch 31 - iter 38/386 - loss 0.13605364 - samples/sec: 112.39 - lr: 0.100000 |
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2022-11-06 21:10:43,072 epoch 31 - iter 76/386 - loss 0.13129275 - samples/sec: 117.05 - lr: 0.100000 |
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2022-11-06 21:10:48,560 epoch 31 - iter 114/386 - loss 0.12929537 - samples/sec: 110.85 - lr: 0.100000 |
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2022-11-06 21:10:54,309 epoch 31 - iter 152/386 - loss 0.13464118 - samples/sec: 105.81 - lr: 0.100000 |
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2022-11-06 21:11:00,243 epoch 31 - iter 190/386 - loss 0.13449220 - samples/sec: 102.51 - lr: 0.100000 |
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2022-11-06 21:11:05,899 epoch 31 - iter 228/386 - loss 0.13490655 - samples/sec: 107.54 - lr: 0.100000 |
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2022-11-06 21:11:11,421 epoch 31 - iter 266/386 - loss 0.13724499 - samples/sec: 110.18 - lr: 0.100000 |
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2022-11-06 21:11:16,750 epoch 31 - iter 304/386 - loss 0.13669783 - samples/sec: 114.14 - lr: 0.100000 |
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2022-11-06 21:11:22,824 epoch 31 - iter 342/386 - loss 0.13557873 - samples/sec: 100.15 - lr: 0.100000 |
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2022-11-06 21:11:28,281 epoch 31 - iter 380/386 - loss 0.13537335 - samples/sec: 111.48 - lr: 0.100000 |
|
2022-11-06 21:11:29,086 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:11:29,086 EPOCH 31 done: loss 0.1352 - lr 0.100000 |
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2022-11-06 21:11:38,570 Evaluating as a multi-label problem: False |
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2022-11-06 21:11:38,683 TEST : loss 0.07867585122585297 - f1-score (micro avg) 0.9759 |
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2022-11-06 21:11:38,795 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:11:39,003 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:11:44,555 epoch 32 - iter 38/386 - loss 0.13232513 - samples/sec: 109.61 - lr: 0.100000 |
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2022-11-06 21:11:49,687 epoch 32 - iter 76/386 - loss 0.13482951 - samples/sec: 118.55 - lr: 0.100000 |
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2022-11-06 21:11:54,993 epoch 32 - iter 114/386 - loss 0.13304503 - samples/sec: 114.65 - lr: 0.100000 |
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2022-11-06 21:12:01,031 epoch 32 - iter 152/386 - loss 0.13218221 - samples/sec: 100.74 - lr: 0.100000 |
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2022-11-06 21:12:06,365 epoch 32 - iter 190/386 - loss 0.13670654 - samples/sec: 114.04 - lr: 0.100000 |
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2022-11-06 21:12:11,993 epoch 32 - iter 228/386 - loss 0.13752981 - samples/sec: 108.10 - lr: 0.100000 |
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2022-11-06 21:12:17,882 epoch 32 - iter 266/386 - loss 0.13855191 - samples/sec: 103.29 - lr: 0.100000 |
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2022-11-06 21:12:23,269 epoch 32 - iter 304/386 - loss 0.13809400 - samples/sec: 112.93 - lr: 0.100000 |
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2022-11-06 21:12:29,310 epoch 32 - iter 342/386 - loss 0.13822772 - samples/sec: 100.71 - lr: 0.100000 |
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2022-11-06 21:12:34,964 epoch 32 - iter 380/386 - loss 0.13783689 - samples/sec: 107.59 - lr: 0.100000 |
|
2022-11-06 21:12:35,755 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:12:35,755 EPOCH 32 done: loss 0.1380 - lr 0.100000 |
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2022-11-06 21:12:45,245 Evaluating as a multi-label problem: False |
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2022-11-06 21:12:45,358 TEST : loss 0.07559281587600708 - f1-score (micro avg) 0.9764 |
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2022-11-06 21:12:45,470 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 21:12:45,673 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:12:50,680 epoch 33 - iter 38/386 - loss 0.13040322 - samples/sec: 121.52 - lr: 0.100000 |
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2022-11-06 21:12:56,389 epoch 33 - iter 76/386 - loss 0.13221927 - samples/sec: 106.56 - lr: 0.100000 |
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2022-11-06 21:13:01,972 epoch 33 - iter 114/386 - loss 0.13390827 - samples/sec: 108.96 - lr: 0.100000 |
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2022-11-06 21:13:07,263 epoch 33 - iter 152/386 - loss 0.13364135 - samples/sec: 114.98 - lr: 0.100000 |
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2022-11-06 21:13:12,446 epoch 33 - iter 190/386 - loss 0.13402240 - samples/sec: 117.38 - lr: 0.100000 |
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2022-11-06 21:13:18,032 epoch 33 - iter 228/386 - loss 0.13390599 - samples/sec: 108.91 - lr: 0.100000 |
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2022-11-06 21:13:23,570 epoch 33 - iter 266/386 - loss 0.13400107 - samples/sec: 109.84 - lr: 0.100000 |
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2022-11-06 21:13:29,197 epoch 33 - iter 304/386 - loss 0.13416777 - samples/sec: 108.10 - lr: 0.100000 |
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2022-11-06 21:13:35,233 epoch 33 - iter 342/386 - loss 0.13495150 - samples/sec: 100.79 - lr: 0.100000 |
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2022-11-06 21:13:41,146 epoch 33 - iter 380/386 - loss 0.13447871 - samples/sec: 102.87 - lr: 0.100000 |
|
2022-11-06 21:13:41,959 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:13:41,959 EPOCH 33 done: loss 0.1345 - lr 0.100000 |
|
2022-11-06 21:13:51,410 Evaluating as a multi-label problem: False |
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2022-11-06 21:13:51,526 TEST : loss 0.07484747469425201 - f1-score (micro avg) 0.9777 |
|
2022-11-06 21:13:51,639 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:13:51,845 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:13:58,087 epoch 34 - iter 38/386 - loss 0.12716848 - samples/sec: 97.48 - lr: 0.100000 |
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2022-11-06 21:14:03,926 epoch 34 - iter 76/386 - loss 0.13247563 - samples/sec: 104.19 - lr: 0.100000 |
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2022-11-06 21:14:09,453 epoch 34 - iter 114/386 - loss 0.13110225 - samples/sec: 110.06 - lr: 0.100000 |
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2022-11-06 21:14:14,599 epoch 34 - iter 152/386 - loss 0.13129140 - samples/sec: 118.22 - lr: 0.100000 |
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2022-11-06 21:14:19,723 epoch 34 - iter 190/386 - loss 0.13341774 - samples/sec: 118.72 - lr: 0.100000 |
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2022-11-06 21:14:25,406 epoch 34 - iter 228/386 - loss 0.13308897 - samples/sec: 107.05 - lr: 0.100000 |
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2022-11-06 21:14:30,738 epoch 34 - iter 266/386 - loss 0.13388475 - samples/sec: 114.09 - lr: 0.100000 |
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2022-11-06 21:14:36,691 epoch 34 - iter 304/386 - loss 0.13500382 - samples/sec: 102.19 - lr: 0.100000 |
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2022-11-06 21:14:42,091 epoch 34 - iter 342/386 - loss 0.13561086 - samples/sec: 112.66 - lr: 0.100000 |
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2022-11-06 21:14:47,903 epoch 34 - iter 380/386 - loss 0.13482125 - samples/sec: 104.67 - lr: 0.100000 |
|
2022-11-06 21:14:48,710 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:14:48,711 EPOCH 34 done: loss 0.1347 - lr 0.100000 |
|
2022-11-06 21:14:58,212 Evaluating as a multi-label problem: False |
|
2022-11-06 21:14:58,326 TEST : loss 0.07798200100660324 - f1-score (micro avg) 0.9772 |
|
2022-11-06 21:14:58,438 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 21:14:58,646 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:15:03,999 epoch 35 - iter 38/386 - loss 0.12669705 - samples/sec: 113.66 - lr: 0.100000 |
|
2022-11-06 21:15:09,226 epoch 35 - iter 76/386 - loss 0.12803323 - samples/sec: 116.39 - lr: 0.100000 |
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2022-11-06 21:15:14,490 epoch 35 - iter 114/386 - loss 0.13240979 - samples/sec: 115.59 - lr: 0.100000 |
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2022-11-06 21:15:19,801 epoch 35 - iter 152/386 - loss 0.13315680 - samples/sec: 114.53 - lr: 0.100000 |
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2022-11-06 21:15:25,186 epoch 35 - iter 190/386 - loss 0.13257909 - samples/sec: 112.99 - lr: 0.100000 |
|
2022-11-06 21:15:31,186 epoch 35 - iter 228/386 - loss 0.13326997 - samples/sec: 101.37 - lr: 0.100000 |
|
2022-11-06 21:15:36,633 epoch 35 - iter 266/386 - loss 0.13333582 - samples/sec: 111.69 - lr: 0.100000 |
|
2022-11-06 21:15:42,519 epoch 35 - iter 304/386 - loss 0.13407603 - samples/sec: 103.34 - lr: 0.100000 |
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2022-11-06 21:15:47,912 epoch 35 - iter 342/386 - loss 0.13477046 - samples/sec: 112.81 - lr: 0.100000 |
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2022-11-06 21:15:54,149 epoch 35 - iter 380/386 - loss 0.13462222 - samples/sec: 97.53 - lr: 0.100000 |
|
2022-11-06 21:15:55,071 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:15:55,071 EPOCH 35 done: loss 0.1344 - lr 0.100000 |
|
2022-11-06 21:16:06,985 Evaluating as a multi-label problem: False |
|
2022-11-06 21:16:07,099 TEST : loss 0.07759656012058258 - f1-score (micro avg) 0.9763 |
|
2022-11-06 21:16:07,211 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:16:07,415 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:16:13,125 epoch 36 - iter 38/386 - loss 0.14084251 - samples/sec: 106.55 - lr: 0.100000 |
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2022-11-06 21:16:18,426 epoch 36 - iter 76/386 - loss 0.13560492 - samples/sec: 114.77 - lr: 0.100000 |
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2022-11-06 21:16:23,844 epoch 36 - iter 114/386 - loss 0.13425714 - samples/sec: 112.28 - lr: 0.100000 |
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2022-11-06 21:16:29,425 epoch 36 - iter 152/386 - loss 0.13443528 - samples/sec: 108.98 - lr: 0.100000 |
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2022-11-06 21:16:35,416 epoch 36 - iter 190/386 - loss 0.13544237 - samples/sec: 101.55 - lr: 0.100000 |
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2022-11-06 21:16:40,715 epoch 36 - iter 228/386 - loss 0.13445681 - samples/sec: 114.79 - lr: 0.100000 |
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2022-11-06 21:16:46,197 epoch 36 - iter 266/386 - loss 0.13370809 - samples/sec: 110.98 - lr: 0.100000 |
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2022-11-06 21:16:52,085 epoch 36 - iter 304/386 - loss 0.13356780 - samples/sec: 103.30 - lr: 0.100000 |
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2022-11-06 21:16:57,690 epoch 36 - iter 342/386 - loss 0.13324128 - samples/sec: 108.54 - lr: 0.100000 |
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2022-11-06 21:17:03,316 epoch 36 - iter 380/386 - loss 0.13276034 - samples/sec: 108.12 - lr: 0.100000 |
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2022-11-06 21:17:04,142 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:17:04,143 EPOCH 36 done: loss 0.1328 - lr 0.100000 |
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2022-11-06 21:17:13,677 Evaluating as a multi-label problem: False |
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2022-11-06 21:17:13,791 TEST : loss 0.07676690816879272 - f1-score (micro avg) 0.9773 |
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2022-11-06 21:17:13,903 BAD EPOCHS (no improvement): 0 |
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2022-11-06 21:17:14,112 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:17:20,098 epoch 37 - iter 38/386 - loss 0.11773268 - samples/sec: 101.66 - lr: 0.100000 |
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2022-11-06 21:17:25,549 epoch 37 - iter 76/386 - loss 0.12268172 - samples/sec: 111.60 - lr: 0.100000 |
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2022-11-06 21:17:31,263 epoch 37 - iter 114/386 - loss 0.12196934 - samples/sec: 106.46 - lr: 0.100000 |
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2022-11-06 21:17:36,935 epoch 37 - iter 152/386 - loss 0.12469575 - samples/sec: 107.26 - lr: 0.100000 |
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2022-11-06 21:17:42,684 epoch 37 - iter 190/386 - loss 0.12632570 - samples/sec: 105.81 - lr: 0.100000 |
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2022-11-06 21:17:48,000 epoch 37 - iter 228/386 - loss 0.12650076 - samples/sec: 114.42 - lr: 0.100000 |
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2022-11-06 21:17:52,778 epoch 37 - iter 266/386 - loss 0.12751872 - samples/sec: 127.35 - lr: 0.100000 |
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2022-11-06 21:17:58,664 epoch 37 - iter 304/386 - loss 0.12835283 - samples/sec: 103.34 - lr: 0.100000 |
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2022-11-06 21:18:04,258 epoch 37 - iter 342/386 - loss 0.12751420 - samples/sec: 108.76 - lr: 0.100000 |
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2022-11-06 21:18:10,061 epoch 37 - iter 380/386 - loss 0.12880953 - samples/sec: 104.82 - lr: 0.100000 |
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2022-11-06 21:18:10,878 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:18:10,878 EPOCH 37 done: loss 0.1289 - lr 0.100000 |
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2022-11-06 21:18:20,270 Evaluating as a multi-label problem: False |
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2022-11-06 21:18:20,386 TEST : loss 0.07300665974617004 - f1-score (micro avg) 0.978 |
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2022-11-06 21:18:20,498 BAD EPOCHS (no improvement): 0 |
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2022-11-06 21:18:20,713 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:18:25,955 epoch 38 - iter 38/386 - loss 0.12656382 - samples/sec: 116.08 - lr: 0.100000 |
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2022-11-06 21:18:31,778 epoch 38 - iter 76/386 - loss 0.12664169 - samples/sec: 104.47 - lr: 0.100000 |
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2022-11-06 21:18:37,249 epoch 38 - iter 114/386 - loss 0.12657923 - samples/sec: 111.19 - lr: 0.100000 |
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2022-11-06 21:18:43,101 epoch 38 - iter 152/386 - loss 0.12572572 - samples/sec: 103.96 - lr: 0.100000 |
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2022-11-06 21:18:49,038 epoch 38 - iter 190/386 - loss 0.12654161 - samples/sec: 102.46 - lr: 0.100000 |
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2022-11-06 21:18:54,901 epoch 38 - iter 228/386 - loss 0.12749062 - samples/sec: 103.74 - lr: 0.100000 |
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2022-11-06 21:19:00,492 epoch 38 - iter 266/386 - loss 0.12772509 - samples/sec: 108.81 - lr: 0.100000 |
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2022-11-06 21:19:05,602 epoch 38 - iter 304/386 - loss 0.12844144 - samples/sec: 119.05 - lr: 0.100000 |
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2022-11-06 21:19:10,460 epoch 38 - iter 342/386 - loss 0.12831778 - samples/sec: 125.23 - lr: 0.100000 |
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2022-11-06 21:19:16,192 epoch 38 - iter 380/386 - loss 0.12827157 - samples/sec: 106.12 - lr: 0.100000 |
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2022-11-06 21:19:16,916 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:19:16,916 EPOCH 38 done: loss 0.1286 - lr 0.100000 |
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2022-11-06 21:19:26,445 Evaluating as a multi-label problem: False |
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2022-11-06 21:19:26,560 TEST : loss 0.07631804794073105 - f1-score (micro avg) 0.9765 |
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2022-11-06 21:19:26,673 BAD EPOCHS (no improvement): 0 |
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2022-11-06 21:19:26,873 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:19:32,474 epoch 39 - iter 38/386 - loss 0.12921879 - samples/sec: 108.64 - lr: 0.100000 |
|
2022-11-06 21:19:38,030 epoch 39 - iter 76/386 - loss 0.12550183 - samples/sec: 109.50 - lr: 0.100000 |
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2022-11-06 21:19:43,651 epoch 39 - iter 114/386 - loss 0.12590097 - samples/sec: 108.22 - lr: 0.100000 |
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2022-11-06 21:19:49,937 epoch 39 - iter 152/386 - loss 0.12453781 - samples/sec: 96.76 - lr: 0.100000 |
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2022-11-06 21:19:55,059 epoch 39 - iter 190/386 - loss 0.12681373 - samples/sec: 118.78 - lr: 0.100000 |
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2022-11-06 21:20:00,742 epoch 39 - iter 228/386 - loss 0.12644162 - samples/sec: 107.04 - lr: 0.100000 |
|
2022-11-06 21:20:06,147 epoch 39 - iter 266/386 - loss 0.12619254 - samples/sec: 112.55 - lr: 0.100000 |
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2022-11-06 21:20:11,462 epoch 39 - iter 304/386 - loss 0.12768228 - samples/sec: 114.46 - lr: 0.100000 |
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2022-11-06 21:20:16,796 epoch 39 - iter 342/386 - loss 0.12841007 - samples/sec: 114.06 - lr: 0.100000 |
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2022-11-06 21:20:22,820 epoch 39 - iter 380/386 - loss 0.12930063 - samples/sec: 100.98 - lr: 0.100000 |
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2022-11-06 21:20:23,811 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:20:23,811 EPOCH 39 done: loss 0.1297 - lr 0.100000 |
|
2022-11-06 21:20:34,264 Evaluating as a multi-label problem: False |
|
2022-11-06 21:20:34,385 TEST : loss 0.07472442835569382 - f1-score (micro avg) 0.9769 |
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2022-11-06 21:20:34,499 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 21:20:34,700 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:20:40,752 epoch 40 - iter 38/386 - loss 0.12268551 - samples/sec: 100.55 - lr: 0.100000 |
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2022-11-06 21:20:47,598 epoch 40 - iter 76/386 - loss 0.12238748 - samples/sec: 88.84 - lr: 0.100000 |
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2022-11-06 21:20:53,304 epoch 40 - iter 114/386 - loss 0.12365842 - samples/sec: 106.63 - lr: 0.100000 |
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2022-11-06 21:20:59,388 epoch 40 - iter 152/386 - loss 0.12125446 - samples/sec: 99.98 - lr: 0.100000 |
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2022-11-06 21:21:05,617 epoch 40 - iter 190/386 - loss 0.12154079 - samples/sec: 97.67 - lr: 0.100000 |
|
2022-11-06 21:21:11,161 epoch 40 - iter 228/386 - loss 0.12124347 - samples/sec: 109.71 - lr: 0.100000 |
|
2022-11-06 21:21:17,542 epoch 40 - iter 266/386 - loss 0.12335241 - samples/sec: 95.34 - lr: 0.100000 |
|
2022-11-06 21:21:23,746 epoch 40 - iter 304/386 - loss 0.12514150 - samples/sec: 98.04 - lr: 0.100000 |
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2022-11-06 21:21:29,748 epoch 40 - iter 342/386 - loss 0.12565763 - samples/sec: 101.36 - lr: 0.100000 |
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2022-11-06 21:21:35,962 epoch 40 - iter 380/386 - loss 0.12620808 - samples/sec: 97.90 - lr: 0.100000 |
|
2022-11-06 21:21:36,822 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:21:36,822 EPOCH 40 done: loss 0.1260 - lr 0.100000 |
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2022-11-06 21:21:47,770 Evaluating as a multi-label problem: False |
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2022-11-06 21:21:47,888 TEST : loss 0.0739121362566948 - f1-score (micro avg) 0.9773 |
|
2022-11-06 21:21:48,002 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:21:48,214 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:21:54,367 epoch 41 - iter 38/386 - loss 0.12501690 - samples/sec: 98.87 - lr: 0.100000 |
|
2022-11-06 21:21:59,976 epoch 41 - iter 76/386 - loss 0.12864011 - samples/sec: 108.46 - lr: 0.100000 |
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2022-11-06 21:22:05,669 epoch 41 - iter 114/386 - loss 0.12787936 - samples/sec: 106.86 - lr: 0.100000 |
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2022-11-06 21:22:11,608 epoch 41 - iter 152/386 - loss 0.12923740 - samples/sec: 102.43 - lr: 0.100000 |
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2022-11-06 21:22:17,559 epoch 41 - iter 190/386 - loss 0.12849211 - samples/sec: 102.21 - lr: 0.100000 |
|
2022-11-06 21:22:23,015 epoch 41 - iter 228/386 - loss 0.12815326 - samples/sec: 111.50 - lr: 0.100000 |
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2022-11-06 21:22:28,588 epoch 41 - iter 266/386 - loss 0.12708207 - samples/sec: 110.00 - lr: 0.100000 |
|
2022-11-06 21:22:34,117 epoch 41 - iter 304/386 - loss 0.12568639 - samples/sec: 110.03 - lr: 0.100000 |
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2022-11-06 21:22:40,037 epoch 41 - iter 342/386 - loss 0.12439832 - samples/sec: 102.75 - lr: 0.100000 |
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2022-11-06 21:22:45,593 epoch 41 - iter 380/386 - loss 0.12537910 - samples/sec: 109.51 - lr: 0.100000 |
|
2022-11-06 21:22:46,444 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:22:46,444 EPOCH 41 done: loss 0.1253 - lr 0.100000 |
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2022-11-06 21:22:56,038 Evaluating as a multi-label problem: False |
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2022-11-06 21:22:56,155 TEST : loss 0.0780162438750267 - f1-score (micro avg) 0.977 |
|
2022-11-06 21:22:56,269 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:22:56,482 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:23:02,363 epoch 42 - iter 38/386 - loss 0.11149869 - samples/sec: 103.47 - lr: 0.100000 |
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2022-11-06 21:23:07,895 epoch 42 - iter 76/386 - loss 0.11748343 - samples/sec: 109.98 - lr: 0.100000 |
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2022-11-06 21:23:13,346 epoch 42 - iter 114/386 - loss 0.11649259 - samples/sec: 111.59 - lr: 0.100000 |
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2022-11-06 21:23:18,275 epoch 42 - iter 152/386 - loss 0.11698177 - samples/sec: 123.44 - lr: 0.100000 |
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2022-11-06 21:23:23,563 epoch 42 - iter 190/386 - loss 0.11887342 - samples/sec: 115.03 - lr: 0.100000 |
|
2022-11-06 21:23:29,173 epoch 42 - iter 228/386 - loss 0.11677996 - samples/sec: 108.44 - lr: 0.100000 |
|
2022-11-06 21:23:34,579 epoch 42 - iter 266/386 - loss 0.11824350 - samples/sec: 112.54 - lr: 0.100000 |
|
2022-11-06 21:23:40,055 epoch 42 - iter 304/386 - loss 0.12008683 - samples/sec: 111.08 - lr: 0.100000 |
|
2022-11-06 21:23:45,880 epoch 42 - iter 342/386 - loss 0.12062932 - samples/sec: 104.43 - lr: 0.100000 |
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2022-11-06 21:23:51,979 epoch 42 - iter 380/386 - loss 0.12229146 - samples/sec: 99.74 - lr: 0.100000 |
|
2022-11-06 21:23:52,834 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:23:52,834 EPOCH 42 done: loss 0.1220 - lr 0.100000 |
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2022-11-06 21:24:02,444 Evaluating as a multi-label problem: False |
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2022-11-06 21:24:02,562 TEST : loss 0.07854187488555908 - f1-score (micro avg) 0.976 |
|
2022-11-06 21:24:02,674 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:24:02,884 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:24:08,148 epoch 43 - iter 38/386 - loss 0.11958608 - samples/sec: 115.61 - lr: 0.100000 |
|
2022-11-06 21:24:13,398 epoch 43 - iter 76/386 - loss 0.11836372 - samples/sec: 115.88 - lr: 0.100000 |
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2022-11-06 21:24:19,459 epoch 43 - iter 114/386 - loss 0.12201423 - samples/sec: 100.36 - lr: 0.100000 |
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2022-11-06 21:24:25,282 epoch 43 - iter 152/386 - loss 0.12318619 - samples/sec: 104.48 - lr: 0.100000 |
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2022-11-06 21:24:30,615 epoch 43 - iter 190/386 - loss 0.12337366 - samples/sec: 114.06 - lr: 0.100000 |
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2022-11-06 21:24:36,294 epoch 43 - iter 228/386 - loss 0.12486417 - samples/sec: 107.83 - lr: 0.100000 |
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2022-11-06 21:24:41,939 epoch 43 - iter 266/386 - loss 0.12427762 - samples/sec: 107.77 - lr: 0.100000 |
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2022-11-06 21:24:47,463 epoch 43 - iter 304/386 - loss 0.12320286 - samples/sec: 110.98 - lr: 0.100000 |
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2022-11-06 21:24:53,194 epoch 43 - iter 342/386 - loss 0.12386685 - samples/sec: 106.14 - lr: 0.100000 |
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2022-11-06 21:24:58,726 epoch 43 - iter 380/386 - loss 0.12403804 - samples/sec: 109.98 - lr: 0.100000 |
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2022-11-06 21:24:59,622 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:24:59,622 EPOCH 43 done: loss 0.1240 - lr 0.100000 |
|
2022-11-06 21:25:09,220 Evaluating as a multi-label problem: False |
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2022-11-06 21:25:09,336 TEST : loss 0.0756213441491127 - f1-score (micro avg) 0.9772 |
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2022-11-06 21:25:09,450 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 21:25:09,661 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:25:14,975 epoch 44 - iter 38/386 - loss 0.11529806 - samples/sec: 114.50 - lr: 0.100000 |
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2022-11-06 21:25:21,233 epoch 44 - iter 76/386 - loss 0.12011694 - samples/sec: 97.22 - lr: 0.100000 |
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2022-11-06 21:25:27,381 epoch 44 - iter 114/386 - loss 0.11971319 - samples/sec: 98.93 - lr: 0.100000 |
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2022-11-06 21:25:33,175 epoch 44 - iter 152/386 - loss 0.11990878 - samples/sec: 105.00 - lr: 0.100000 |
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2022-11-06 21:25:38,881 epoch 44 - iter 190/386 - loss 0.12065174 - samples/sec: 106.62 - lr: 0.100000 |
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2022-11-06 21:25:44,099 epoch 44 - iter 228/386 - loss 0.11906558 - samples/sec: 116.58 - lr: 0.100000 |
|
2022-11-06 21:25:49,404 epoch 44 - iter 266/386 - loss 0.12058134 - samples/sec: 115.19 - lr: 0.100000 |
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2022-11-06 21:25:54,627 epoch 44 - iter 304/386 - loss 0.12038138 - samples/sec: 116.49 - lr: 0.100000 |
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2022-11-06 21:25:59,973 epoch 44 - iter 342/386 - loss 0.12033364 - samples/sec: 113.80 - lr: 0.100000 |
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2022-11-06 21:26:05,652 epoch 44 - iter 380/386 - loss 0.12198193 - samples/sec: 107.12 - lr: 0.100000 |
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2022-11-06 21:26:06,529 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:26:06,530 EPOCH 44 done: loss 0.1220 - lr 0.100000 |
|
2022-11-06 21:26:16,050 Evaluating as a multi-label problem: False |
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2022-11-06 21:26:16,167 TEST : loss 0.07966844737529755 - f1-score (micro avg) 0.9765 |
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2022-11-06 21:26:16,280 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:26:16,483 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:26:22,198 epoch 45 - iter 38/386 - loss 0.11658074 - samples/sec: 106.47 - lr: 0.100000 |
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2022-11-06 21:26:27,956 epoch 45 - iter 76/386 - loss 0.11810186 - samples/sec: 105.66 - lr: 0.100000 |
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2022-11-06 21:26:33,511 epoch 45 - iter 114/386 - loss 0.11998494 - samples/sec: 109.51 - lr: 0.100000 |
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2022-11-06 21:26:39,132 epoch 45 - iter 152/386 - loss 0.11772619 - samples/sec: 108.22 - lr: 0.100000 |
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2022-11-06 21:26:44,693 epoch 45 - iter 190/386 - loss 0.11807594 - samples/sec: 109.41 - lr: 0.100000 |
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2022-11-06 21:26:50,190 epoch 45 - iter 228/386 - loss 0.11906856 - samples/sec: 110.67 - lr: 0.100000 |
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2022-11-06 21:26:55,645 epoch 45 - iter 266/386 - loss 0.12077577 - samples/sec: 111.52 - lr: 0.100000 |
|
2022-11-06 21:27:01,272 epoch 45 - iter 304/386 - loss 0.12018970 - samples/sec: 108.11 - lr: 0.100000 |
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2022-11-06 21:27:06,688 epoch 45 - iter 342/386 - loss 0.12045177 - samples/sec: 112.33 - lr: 0.100000 |
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2022-11-06 21:27:12,362 epoch 45 - iter 380/386 - loss 0.12097869 - samples/sec: 107.20 - lr: 0.100000 |
|
2022-11-06 21:27:13,161 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:27:13,161 EPOCH 45 done: loss 0.1209 - lr 0.100000 |
|
2022-11-06 21:27:22,937 Evaluating as a multi-label problem: False |
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2022-11-06 21:27:23,053 TEST : loss 0.07720887660980225 - f1-score (micro avg) 0.9767 |
|
2022-11-06 21:27:23,166 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:27:23,377 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:27:29,128 epoch 46 - iter 38/386 - loss 0.11581804 - samples/sec: 105.81 - lr: 0.100000 |
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2022-11-06 21:27:34,828 epoch 46 - iter 76/386 - loss 0.11872404 - samples/sec: 106.72 - lr: 0.100000 |
|
2022-11-06 21:27:39,690 epoch 46 - iter 114/386 - loss 0.11995258 - samples/sec: 125.14 - lr: 0.100000 |
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2022-11-06 21:27:45,311 epoch 46 - iter 152/386 - loss 0.12179851 - samples/sec: 108.22 - lr: 0.100000 |
|
2022-11-06 21:27:51,300 epoch 46 - iter 190/386 - loss 0.12292524 - samples/sec: 101.57 - lr: 0.100000 |
|
2022-11-06 21:27:57,100 epoch 46 - iter 228/386 - loss 0.12271512 - samples/sec: 104.88 - lr: 0.100000 |
|
2022-11-06 21:28:02,842 epoch 46 - iter 266/386 - loss 0.12196746 - samples/sec: 105.95 - lr: 0.100000 |
|
2022-11-06 21:28:08,370 epoch 46 - iter 304/386 - loss 0.12271587 - samples/sec: 110.06 - lr: 0.100000 |
|
2022-11-06 21:28:13,125 epoch 46 - iter 342/386 - loss 0.12309745 - samples/sec: 127.93 - lr: 0.100000 |
|
2022-11-06 21:28:18,470 epoch 46 - iter 380/386 - loss 0.12348590 - samples/sec: 113.83 - lr: 0.100000 |
|
2022-11-06 21:28:19,306 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:28:19,307 EPOCH 46 done: loss 0.1233 - lr 0.100000 |
|
2022-11-06 21:28:31,227 Evaluating as a multi-label problem: False |
|
2022-11-06 21:28:31,344 TEST : loss 0.07568249851465225 - f1-score (micro avg) 0.9774 |
|
2022-11-06 21:28:31,457 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 21:28:31,669 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:28:37,650 epoch 47 - iter 38/386 - loss 0.11595339 - samples/sec: 101.73 - lr: 0.100000 |
|
2022-11-06 21:28:43,362 epoch 47 - iter 76/386 - loss 0.11709559 - samples/sec: 106.50 - lr: 0.100000 |
|
2022-11-06 21:28:49,223 epoch 47 - iter 114/386 - loss 0.11756609 - samples/sec: 103.79 - lr: 0.100000 |
|
2022-11-06 21:28:54,635 epoch 47 - iter 152/386 - loss 0.12033252 - samples/sec: 112.41 - lr: 0.100000 |
|
2022-11-06 21:29:00,052 epoch 47 - iter 190/386 - loss 0.12025189 - samples/sec: 112.30 - lr: 0.100000 |
|
2022-11-06 21:29:05,678 epoch 47 - iter 228/386 - loss 0.11965504 - samples/sec: 108.12 - lr: 0.100000 |
|
2022-11-06 21:29:11,257 epoch 47 - iter 266/386 - loss 0.11906688 - samples/sec: 109.05 - lr: 0.100000 |
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2022-11-06 21:29:16,838 epoch 47 - iter 304/386 - loss 0.11868831 - samples/sec: 109.00 - lr: 0.100000 |
|
2022-11-06 21:29:21,901 epoch 47 - iter 342/386 - loss 0.12035505 - samples/sec: 120.16 - lr: 0.100000 |
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2022-11-06 21:29:27,022 epoch 47 - iter 380/386 - loss 0.12021009 - samples/sec: 118.79 - lr: 0.100000 |
|
2022-11-06 21:29:27,884 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:29:27,884 EPOCH 47 done: loss 0.1203 - lr 0.100000 |
|
2022-11-06 21:29:37,446 Evaluating as a multi-label problem: False |
|
2022-11-06 21:29:37,563 TEST : loss 0.07547062635421753 - f1-score (micro avg) 0.9775 |
|
2022-11-06 21:29:37,678 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:29:37,876 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:29:43,653 epoch 48 - iter 38/386 - loss 0.12227377 - samples/sec: 105.33 - lr: 0.100000 |
|
2022-11-06 21:29:49,140 epoch 48 - iter 76/386 - loss 0.12056539 - samples/sec: 110.87 - lr: 0.100000 |
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2022-11-06 21:29:54,836 epoch 48 - iter 114/386 - loss 0.11941017 - samples/sec: 106.80 - lr: 0.100000 |
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2022-11-06 21:30:00,821 epoch 48 - iter 152/386 - loss 0.12095295 - samples/sec: 101.64 - lr: 0.100000 |
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2022-11-06 21:30:06,274 epoch 48 - iter 190/386 - loss 0.12128609 - samples/sec: 111.55 - lr: 0.100000 |
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2022-11-06 21:30:12,004 epoch 48 - iter 228/386 - loss 0.12113142 - samples/sec: 106.17 - lr: 0.100000 |
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2022-11-06 21:30:17,705 epoch 48 - iter 266/386 - loss 0.12022908 - samples/sec: 106.71 - lr: 0.100000 |
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2022-11-06 21:30:23,040 epoch 48 - iter 304/386 - loss 0.12018651 - samples/sec: 114.03 - lr: 0.100000 |
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2022-11-06 21:30:28,146 epoch 48 - iter 342/386 - loss 0.12015658 - samples/sec: 119.16 - lr: 0.100000 |
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2022-11-06 21:30:33,425 epoch 48 - iter 380/386 - loss 0.12050812 - samples/sec: 115.24 - lr: 0.100000 |
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2022-11-06 21:30:34,660 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:30:34,660 EPOCH 48 done: loss 0.1204 - lr 0.100000 |
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2022-11-06 21:30:43,888 Evaluating as a multi-label problem: False |
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2022-11-06 21:30:44,005 TEST : loss 0.07593300938606262 - f1-score (micro avg) 0.9779 |
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2022-11-06 21:30:44,119 BAD EPOCHS (no improvement): 1 |
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2022-11-06 21:30:44,324 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:30:49,608 epoch 49 - iter 38/386 - loss 0.11311434 - samples/sec: 115.17 - lr: 0.100000 |
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2022-11-06 21:30:55,068 epoch 49 - iter 76/386 - loss 0.11893316 - samples/sec: 111.43 - lr: 0.100000 |
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2022-11-06 21:31:00,591 epoch 49 - iter 114/386 - loss 0.11886508 - samples/sec: 110.13 - lr: 0.100000 |
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2022-11-06 21:31:06,265 epoch 49 - iter 152/386 - loss 0.11676186 - samples/sec: 107.23 - lr: 0.100000 |
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2022-11-06 21:31:11,933 epoch 49 - iter 190/386 - loss 0.11803846 - samples/sec: 107.32 - lr: 0.100000 |
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2022-11-06 21:31:17,749 epoch 49 - iter 228/386 - loss 0.11884410 - samples/sec: 104.58 - lr: 0.100000 |
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2022-11-06 21:31:23,644 epoch 49 - iter 266/386 - loss 0.11916669 - samples/sec: 103.21 - lr: 0.100000 |
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2022-11-06 21:31:29,531 epoch 49 - iter 304/386 - loss 0.11847528 - samples/sec: 103.32 - lr: 0.100000 |
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2022-11-06 21:31:34,769 epoch 49 - iter 342/386 - loss 0.11839289 - samples/sec: 116.15 - lr: 0.100000 |
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2022-11-06 21:31:40,611 epoch 49 - iter 380/386 - loss 0.11785760 - samples/sec: 104.12 - lr: 0.100000 |
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2022-11-06 21:31:41,537 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:31:41,537 EPOCH 49 done: loss 0.1180 - lr 0.100000 |
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2022-11-06 21:31:50,354 Evaluating as a multi-label problem: False |
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2022-11-06 21:31:50,469 TEST : loss 0.07601259648799896 - f1-score (micro avg) 0.9772 |
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2022-11-06 21:31:50,581 BAD EPOCHS (no improvement): 0 |
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2022-11-06 21:31:50,792 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:31:56,264 epoch 50 - iter 38/386 - loss 0.10859661 - samples/sec: 111.21 - lr: 0.100000 |
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2022-11-06 21:32:01,873 epoch 50 - iter 76/386 - loss 0.11903546 - samples/sec: 108.47 - lr: 0.100000 |
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2022-11-06 21:32:07,333 epoch 50 - iter 114/386 - loss 0.11678697 - samples/sec: 111.42 - lr: 0.100000 |
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2022-11-06 21:32:13,408 epoch 50 - iter 152/386 - loss 0.11600897 - samples/sec: 100.53 - lr: 0.100000 |
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2022-11-06 21:32:19,137 epoch 50 - iter 190/386 - loss 0.11566727 - samples/sec: 106.17 - lr: 0.100000 |
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2022-11-06 21:32:24,914 epoch 50 - iter 228/386 - loss 0.11646796 - samples/sec: 105.31 - lr: 0.100000 |
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2022-11-06 21:32:30,880 epoch 50 - iter 266/386 - loss 0.11725206 - samples/sec: 101.97 - lr: 0.100000 |
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2022-11-06 21:32:36,731 epoch 50 - iter 304/386 - loss 0.11755446 - samples/sec: 103.98 - lr: 0.100000 |
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2022-11-06 21:32:42,356 epoch 50 - iter 342/386 - loss 0.11906673 - samples/sec: 108.14 - lr: 0.100000 |
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2022-11-06 21:32:47,819 epoch 50 - iter 380/386 - loss 0.11887510 - samples/sec: 111.35 - lr: 0.100000 |
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2022-11-06 21:32:48,663 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:32:48,664 EPOCH 50 done: loss 0.1194 - lr 0.100000 |
|
2022-11-06 21:32:57,909 Evaluating as a multi-label problem: False |
|
2022-11-06 21:32:58,026 TEST : loss 0.07529637962579727 - f1-score (micro avg) 0.9777 |
|
2022-11-06 21:32:58,140 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 21:32:58,345 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:33:03,192 epoch 51 - iter 38/386 - loss 0.11452134 - samples/sec: 125.55 - lr: 0.100000 |
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2022-11-06 21:33:08,686 epoch 51 - iter 76/386 - loss 0.11590443 - samples/sec: 110.74 - lr: 0.100000 |
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2022-11-06 21:33:14,440 epoch 51 - iter 114/386 - loss 0.11784341 - samples/sec: 105.72 - lr: 0.100000 |
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2022-11-06 21:33:19,823 epoch 51 - iter 152/386 - loss 0.11705536 - samples/sec: 113.02 - lr: 0.100000 |
|
2022-11-06 21:33:26,045 epoch 51 - iter 190/386 - loss 0.11543878 - samples/sec: 97.76 - lr: 0.100000 |
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2022-11-06 21:33:31,639 epoch 51 - iter 228/386 - loss 0.11612966 - samples/sec: 108.74 - lr: 0.100000 |
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2022-11-06 21:33:37,603 epoch 51 - iter 266/386 - loss 0.11650269 - samples/sec: 102.00 - lr: 0.100000 |
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2022-11-06 21:33:43,427 epoch 51 - iter 304/386 - loss 0.11665112 - samples/sec: 104.46 - lr: 0.100000 |
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2022-11-06 21:33:49,009 epoch 51 - iter 342/386 - loss 0.11723027 - samples/sec: 108.98 - lr: 0.100000 |
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2022-11-06 21:33:54,280 epoch 51 - iter 380/386 - loss 0.11702633 - samples/sec: 115.41 - lr: 0.100000 |
|
2022-11-06 21:33:55,304 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:33:55,304 EPOCH 51 done: loss 0.1173 - lr 0.100000 |
|
2022-11-06 21:34:04,866 Evaluating as a multi-label problem: False |
|
2022-11-06 21:34:04,983 TEST : loss 0.0740566998720169 - f1-score (micro avg) 0.9782 |
|
2022-11-06 21:34:05,097 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:34:05,303 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:34:10,727 epoch 52 - iter 38/386 - loss 0.11155641 - samples/sec: 112.18 - lr: 0.100000 |
|
2022-11-06 21:34:15,463 epoch 52 - iter 76/386 - loss 0.10635453 - samples/sec: 128.47 - lr: 0.100000 |
|
2022-11-06 21:34:21,886 epoch 52 - iter 114/386 - loss 0.10919505 - samples/sec: 94.71 - lr: 0.100000 |
|
2022-11-06 21:34:27,388 epoch 52 - iter 152/386 - loss 0.11221453 - samples/sec: 110.56 - lr: 0.100000 |
|
2022-11-06 21:34:33,430 epoch 52 - iter 190/386 - loss 0.11321872 - samples/sec: 100.69 - lr: 0.100000 |
|
2022-11-06 21:34:39,236 epoch 52 - iter 228/386 - loss 0.11335050 - samples/sec: 104.76 - lr: 0.100000 |
|
2022-11-06 21:34:44,401 epoch 52 - iter 266/386 - loss 0.11362461 - samples/sec: 117.80 - lr: 0.100000 |
|
2022-11-06 21:34:49,871 epoch 52 - iter 304/386 - loss 0.11499895 - samples/sec: 111.23 - lr: 0.100000 |
|
2022-11-06 21:34:55,416 epoch 52 - iter 342/386 - loss 0.11483124 - samples/sec: 109.70 - lr: 0.100000 |
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2022-11-06 21:35:00,713 epoch 52 - iter 380/386 - loss 0.11433020 - samples/sec: 114.85 - lr: 0.100000 |
|
2022-11-06 21:35:01,535 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:35:01,535 EPOCH 52 done: loss 0.1147 - lr 0.100000 |
|
2022-11-06 21:35:11,116 Evaluating as a multi-label problem: False |
|
2022-11-06 21:35:11,232 TEST : loss 0.07622171938419342 - f1-score (micro avg) 0.9777 |
|
2022-11-06 21:35:11,346 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:35:11,555 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:35:16,892 epoch 53 - iter 38/386 - loss 0.11911110 - samples/sec: 114.04 - lr: 0.100000 |
|
2022-11-06 21:35:22,478 epoch 53 - iter 76/386 - loss 0.11354567 - samples/sec: 108.90 - lr: 0.100000 |
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2022-11-06 21:35:27,479 epoch 53 - iter 114/386 - loss 0.11330347 - samples/sec: 121.65 - lr: 0.100000 |
|
2022-11-06 21:35:32,942 epoch 53 - iter 152/386 - loss 0.11457219 - samples/sec: 111.37 - lr: 0.100000 |
|
2022-11-06 21:35:38,294 epoch 53 - iter 190/386 - loss 0.11374010 - samples/sec: 113.67 - lr: 0.100000 |
|
2022-11-06 21:35:44,439 epoch 53 - iter 228/386 - loss 0.11472213 - samples/sec: 98.99 - lr: 0.100000 |
|
2022-11-06 21:35:49,935 epoch 53 - iter 266/386 - loss 0.11446083 - samples/sec: 110.69 - lr: 0.100000 |
|
2022-11-06 21:35:55,321 epoch 53 - iter 304/386 - loss 0.11480098 - samples/sec: 112.95 - lr: 0.100000 |
|
2022-11-06 21:36:01,025 epoch 53 - iter 342/386 - loss 0.11431744 - samples/sec: 106.65 - lr: 0.100000 |
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2022-11-06 21:36:06,693 epoch 53 - iter 380/386 - loss 0.11353443 - samples/sec: 107.33 - lr: 0.100000 |
|
2022-11-06 21:36:07,519 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:36:07,519 EPOCH 53 done: loss 0.1142 - lr 0.100000 |
|
2022-11-06 21:36:17,026 Evaluating as a multi-label problem: False |
|
2022-11-06 21:36:17,170 TEST : loss 0.07737206667661667 - f1-score (micro avg) 0.9773 |
|
2022-11-06 21:36:17,289 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:36:17,516 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:36:23,135 epoch 54 - iter 38/386 - loss 0.11378117 - samples/sec: 108.31 - lr: 0.100000 |
|
2022-11-06 21:36:28,739 epoch 54 - iter 76/386 - loss 0.11354071 - samples/sec: 108.56 - lr: 0.100000 |
|
2022-11-06 21:36:34,885 epoch 54 - iter 114/386 - loss 0.11360766 - samples/sec: 98.97 - lr: 0.100000 |
|
2022-11-06 21:36:40,077 epoch 54 - iter 152/386 - loss 0.11208863 - samples/sec: 117.19 - lr: 0.100000 |
|
2022-11-06 21:36:45,443 epoch 54 - iter 190/386 - loss 0.11447499 - samples/sec: 113.37 - lr: 0.100000 |
|
2022-11-06 21:36:51,117 epoch 54 - iter 228/386 - loss 0.11376877 - samples/sec: 107.22 - lr: 0.100000 |
|
2022-11-06 21:36:56,600 epoch 54 - iter 266/386 - loss 0.11313088 - samples/sec: 110.96 - lr: 0.100000 |
|
2022-11-06 21:37:02,149 epoch 54 - iter 304/386 - loss 0.11250098 - samples/sec: 109.63 - lr: 0.100000 |
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2022-11-06 21:37:07,918 epoch 54 - iter 342/386 - loss 0.11255859 - samples/sec: 105.45 - lr: 0.100000 |
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2022-11-06 21:37:13,229 epoch 54 - iter 380/386 - loss 0.11233373 - samples/sec: 114.54 - lr: 0.100000 |
|
2022-11-06 21:37:13,950 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:37:13,950 EPOCH 54 done: loss 0.1124 - lr 0.100000 |
|
2022-11-06 21:37:23,552 Evaluating as a multi-label problem: False |
|
2022-11-06 21:37:23,669 TEST : loss 0.07463442534208298 - f1-score (micro avg) 0.9784 |
|
2022-11-06 21:37:23,783 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:37:23,992 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:37:29,904 epoch 55 - iter 38/386 - loss 0.11729128 - samples/sec: 102.92 - lr: 0.100000 |
|
2022-11-06 21:37:35,325 epoch 55 - iter 76/386 - loss 0.11251135 - samples/sec: 112.21 - lr: 0.100000 |
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2022-11-06 21:37:41,114 epoch 55 - iter 114/386 - loss 0.10996077 - samples/sec: 105.09 - lr: 0.100000 |
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2022-11-06 21:37:46,552 epoch 55 - iter 152/386 - loss 0.11022640 - samples/sec: 111.86 - lr: 0.100000 |
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2022-11-06 21:37:52,451 epoch 55 - iter 190/386 - loss 0.10943894 - samples/sec: 103.13 - lr: 0.100000 |
|
2022-11-06 21:37:57,751 epoch 55 - iter 228/386 - loss 0.10922557 - samples/sec: 114.80 - lr: 0.100000 |
|
2022-11-06 21:38:03,543 epoch 55 - iter 266/386 - loss 0.11133408 - samples/sec: 105.03 - lr: 0.100000 |
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2022-11-06 21:38:08,825 epoch 55 - iter 304/386 - loss 0.11169533 - samples/sec: 115.16 - lr: 0.100000 |
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2022-11-06 21:38:13,916 epoch 55 - iter 342/386 - loss 0.11234160 - samples/sec: 119.52 - lr: 0.100000 |
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2022-11-06 21:38:19,174 epoch 55 - iter 380/386 - loss 0.11184340 - samples/sec: 115.69 - lr: 0.100000 |
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2022-11-06 21:38:20,110 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:38:20,110 EPOCH 55 done: loss 0.1120 - lr 0.100000 |
|
2022-11-06 21:38:29,735 Evaluating as a multi-label problem: False |
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2022-11-06 21:38:29,852 TEST : loss 0.07638020068407059 - f1-score (micro avg) 0.9794 |
|
2022-11-06 21:38:29,966 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:38:30,172 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:38:36,103 epoch 56 - iter 38/386 - loss 0.11105095 - samples/sec: 102.58 - lr: 0.100000 |
|
2022-11-06 21:38:41,324 epoch 56 - iter 76/386 - loss 0.11292715 - samples/sec: 116.54 - lr: 0.100000 |
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2022-11-06 21:38:46,970 epoch 56 - iter 114/386 - loss 0.11197317 - samples/sec: 107.75 - lr: 0.100000 |
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2022-11-06 21:38:52,483 epoch 56 - iter 152/386 - loss 0.10861220 - samples/sec: 110.34 - lr: 0.100000 |
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2022-11-06 21:38:58,226 epoch 56 - iter 190/386 - loss 0.11033258 - samples/sec: 105.94 - lr: 0.100000 |
|
2022-11-06 21:39:03,351 epoch 56 - iter 228/386 - loss 0.11314777 - samples/sec: 118.70 - lr: 0.100000 |
|
2022-11-06 21:39:08,750 epoch 56 - iter 266/386 - loss 0.11319016 - samples/sec: 112.69 - lr: 0.100000 |
|
2022-11-06 21:39:14,663 epoch 56 - iter 304/386 - loss 0.11310103 - samples/sec: 102.88 - lr: 0.100000 |
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2022-11-06 21:39:19,683 epoch 56 - iter 342/386 - loss 0.11376647 - samples/sec: 121.19 - lr: 0.100000 |
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2022-11-06 21:39:25,519 epoch 56 - iter 380/386 - loss 0.11373646 - samples/sec: 104.22 - lr: 0.100000 |
|
2022-11-06 21:39:26,221 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:39:26,221 EPOCH 56 done: loss 0.1136 - lr 0.100000 |
|
2022-11-06 21:39:38,259 Evaluating as a multi-label problem: False |
|
2022-11-06 21:39:38,376 TEST : loss 0.07799383252859116 - f1-score (micro avg) 0.9774 |
|
2022-11-06 21:39:38,489 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 21:39:38,695 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:39:43,986 epoch 57 - iter 38/386 - loss 0.10619651 - samples/sec: 115.01 - lr: 0.100000 |
|
2022-11-06 21:39:49,781 epoch 57 - iter 76/386 - loss 0.10675645 - samples/sec: 104.98 - lr: 0.100000 |
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2022-11-06 21:39:55,535 epoch 57 - iter 114/386 - loss 0.10678482 - samples/sec: 105.72 - lr: 0.100000 |
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2022-11-06 21:40:01,371 epoch 57 - iter 152/386 - loss 0.10370251 - samples/sec: 104.24 - lr: 0.100000 |
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2022-11-06 21:40:06,881 epoch 57 - iter 190/386 - loss 0.10679265 - samples/sec: 110.41 - lr: 0.100000 |
|
2022-11-06 21:40:12,219 epoch 57 - iter 228/386 - loss 0.10708625 - samples/sec: 113.97 - lr: 0.100000 |
|
2022-11-06 21:40:17,514 epoch 57 - iter 266/386 - loss 0.10891728 - samples/sec: 114.88 - lr: 0.100000 |
|
2022-11-06 21:40:22,851 epoch 57 - iter 304/386 - loss 0.10862710 - samples/sec: 113.99 - lr: 0.100000 |
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2022-11-06 21:40:28,460 epoch 57 - iter 342/386 - loss 0.11015940 - samples/sec: 109.29 - lr: 0.100000 |
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2022-11-06 21:40:34,126 epoch 57 - iter 380/386 - loss 0.10992567 - samples/sec: 107.37 - lr: 0.100000 |
|
2022-11-06 21:40:34,921 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:40:34,921 EPOCH 57 done: loss 0.1101 - lr 0.100000 |
|
2022-11-06 21:40:44,609 Evaluating as a multi-label problem: False |
|
2022-11-06 21:40:44,727 TEST : loss 0.07584260404109955 - f1-score (micro avg) 0.9782 |
|
2022-11-06 21:40:44,841 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:40:45,039 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:40:50,995 epoch 58 - iter 38/386 - loss 0.10393475 - samples/sec: 102.16 - lr: 0.100000 |
|
2022-11-06 21:40:56,311 epoch 58 - iter 76/386 - loss 0.10775986 - samples/sec: 114.45 - lr: 0.100000 |
|
2022-11-06 21:41:01,589 epoch 58 - iter 114/386 - loss 0.10667533 - samples/sec: 115.27 - lr: 0.100000 |
|
2022-11-06 21:41:07,012 epoch 58 - iter 152/386 - loss 0.10719735 - samples/sec: 112.16 - lr: 0.100000 |
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2022-11-06 21:41:12,616 epoch 58 - iter 190/386 - loss 0.10740467 - samples/sec: 108.57 - lr: 0.100000 |
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2022-11-06 21:41:18,171 epoch 58 - iter 228/386 - loss 0.10698504 - samples/sec: 109.50 - lr: 0.100000 |
|
2022-11-06 21:41:23,781 epoch 58 - iter 266/386 - loss 0.10806348 - samples/sec: 108.45 - lr: 0.100000 |
|
2022-11-06 21:41:29,415 epoch 58 - iter 304/386 - loss 0.10804363 - samples/sec: 107.98 - lr: 0.100000 |
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2022-11-06 21:41:34,923 epoch 58 - iter 342/386 - loss 0.10848937 - samples/sec: 110.44 - lr: 0.100000 |
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2022-11-06 21:41:40,542 epoch 58 - iter 380/386 - loss 0.10878650 - samples/sec: 108.27 - lr: 0.100000 |
|
2022-11-06 21:41:41,317 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:41:41,317 EPOCH 58 done: loss 0.1089 - lr 0.100000 |
|
2022-11-06 21:41:51,029 Evaluating as a multi-label problem: False |
|
2022-11-06 21:41:51,146 TEST : loss 0.07553786039352417 - f1-score (micro avg) 0.9777 |
|
2022-11-06 21:41:51,259 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:41:51,476 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:41:57,194 epoch 59 - iter 38/386 - loss 0.10729746 - samples/sec: 106.42 - lr: 0.100000 |
|
2022-11-06 21:42:02,764 epoch 59 - iter 76/386 - loss 0.10706038 - samples/sec: 109.21 - lr: 0.100000 |
|
2022-11-06 21:42:08,164 epoch 59 - iter 114/386 - loss 0.10819463 - samples/sec: 112.65 - lr: 0.100000 |
|
2022-11-06 21:42:13,862 epoch 59 - iter 152/386 - loss 0.11092300 - samples/sec: 107.23 - lr: 0.100000 |
|
2022-11-06 21:42:19,449 epoch 59 - iter 190/386 - loss 0.11033596 - samples/sec: 108.88 - lr: 0.100000 |
|
2022-11-06 21:42:25,236 epoch 59 - iter 228/386 - loss 0.10859445 - samples/sec: 105.11 - lr: 0.100000 |
|
2022-11-06 21:42:30,916 epoch 59 - iter 266/386 - loss 0.10859639 - samples/sec: 107.12 - lr: 0.100000 |
|
2022-11-06 21:42:36,552 epoch 59 - iter 304/386 - loss 0.10838577 - samples/sec: 107.93 - lr: 0.100000 |
|
2022-11-06 21:42:41,937 epoch 59 - iter 342/386 - loss 0.10856409 - samples/sec: 112.96 - lr: 0.100000 |
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2022-11-06 21:42:47,304 epoch 59 - iter 380/386 - loss 0.10888417 - samples/sec: 113.36 - lr: 0.100000 |
|
2022-11-06 21:42:48,120 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:42:48,121 EPOCH 59 done: loss 0.1092 - lr 0.100000 |
|
2022-11-06 21:42:57,722 Evaluating as a multi-label problem: False |
|
2022-11-06 21:42:57,837 TEST : loss 0.07385119795799255 - f1-score (micro avg) 0.9784 |
|
2022-11-06 21:42:57,951 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 21:42:58,161 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:43:03,698 epoch 60 - iter 38/386 - loss 0.10381911 - samples/sec: 109.91 - lr: 0.100000 |
|
2022-11-06 21:43:09,144 epoch 60 - iter 76/386 - loss 0.10904296 - samples/sec: 111.69 - lr: 0.100000 |
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2022-11-06 21:43:14,641 epoch 60 - iter 114/386 - loss 0.10938936 - samples/sec: 111.54 - lr: 0.100000 |
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2022-11-06 21:43:20,357 epoch 60 - iter 152/386 - loss 0.10910729 - samples/sec: 106.41 - lr: 0.100000 |
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2022-11-06 21:43:26,035 epoch 60 - iter 190/386 - loss 0.10992253 - samples/sec: 107.58 - lr: 0.100000 |
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2022-11-06 21:43:31,751 epoch 60 - iter 228/386 - loss 0.10991650 - samples/sec: 106.43 - lr: 0.100000 |
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2022-11-06 21:43:37,812 epoch 60 - iter 266/386 - loss 0.11025661 - samples/sec: 100.37 - lr: 0.100000 |
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2022-11-06 21:43:43,686 epoch 60 - iter 304/386 - loss 0.11020600 - samples/sec: 103.55 - lr: 0.100000 |
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2022-11-06 21:43:48,655 epoch 60 - iter 342/386 - loss 0.11033435 - samples/sec: 122.44 - lr: 0.100000 |
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2022-11-06 21:43:54,168 epoch 60 - iter 380/386 - loss 0.11091046 - samples/sec: 110.35 - lr: 0.100000 |
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2022-11-06 21:43:54,941 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:43:54,941 EPOCH 60 done: loss 0.1108 - lr 0.100000 |
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2022-11-06 21:44:04,122 Evaluating as a multi-label problem: False |
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2022-11-06 21:44:04,237 TEST : loss 0.07543539255857468 - f1-score (micro avg) 0.9787 |
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2022-11-06 21:44:04,349 BAD EPOCHS (no improvement): 2 |
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2022-11-06 21:44:04,562 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:44:10,584 epoch 61 - iter 38/386 - loss 0.12045508 - samples/sec: 101.02 - lr: 0.100000 |
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2022-11-06 21:44:16,219 epoch 61 - iter 76/386 - loss 0.11946764 - samples/sec: 107.97 - lr: 0.100000 |
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2022-11-06 21:44:21,669 epoch 61 - iter 114/386 - loss 0.11543090 - samples/sec: 111.62 - lr: 0.100000 |
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2022-11-06 21:44:27,225 epoch 61 - iter 152/386 - loss 0.11605390 - samples/sec: 109.48 - lr: 0.100000 |
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2022-11-06 21:44:33,223 epoch 61 - iter 190/386 - loss 0.11461676 - samples/sec: 101.42 - lr: 0.100000 |
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2022-11-06 21:44:39,012 epoch 61 - iter 228/386 - loss 0.11382792 - samples/sec: 105.09 - lr: 0.100000 |
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2022-11-06 21:44:44,401 epoch 61 - iter 266/386 - loss 0.11310712 - samples/sec: 113.76 - lr: 0.100000 |
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2022-11-06 21:44:49,754 epoch 61 - iter 304/386 - loss 0.11212259 - samples/sec: 113.65 - lr: 0.100000 |
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2022-11-06 21:44:55,345 epoch 61 - iter 342/386 - loss 0.11132594 - samples/sec: 108.80 - lr: 0.100000 |
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2022-11-06 21:45:00,835 epoch 61 - iter 380/386 - loss 0.11213902 - samples/sec: 110.81 - lr: 0.100000 |
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2022-11-06 21:45:01,644 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:45:01,645 EPOCH 61 done: loss 0.1122 - lr 0.100000 |
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2022-11-06 21:45:10,326 Evaluating as a multi-label problem: False |
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2022-11-06 21:45:10,441 TEST : loss 0.07580757886171341 - f1-score (micro avg) 0.9781 |
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2022-11-06 21:45:10,554 BAD EPOCHS (no improvement): 3 |
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2022-11-06 21:45:10,759 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:45:16,107 epoch 62 - iter 38/386 - loss 0.11185314 - samples/sec: 113.78 - lr: 0.100000 |
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2022-11-06 21:45:21,736 epoch 62 - iter 76/386 - loss 0.10673749 - samples/sec: 108.07 - lr: 0.100000 |
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2022-11-06 21:45:27,662 epoch 62 - iter 114/386 - loss 0.10907345 - samples/sec: 102.66 - lr: 0.100000 |
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2022-11-06 21:45:33,872 epoch 62 - iter 152/386 - loss 0.10767255 - samples/sec: 97.95 - lr: 0.100000 |
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2022-11-06 21:45:39,107 epoch 62 - iter 190/386 - loss 0.10876200 - samples/sec: 116.22 - lr: 0.100000 |
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2022-11-06 21:45:44,769 epoch 62 - iter 228/386 - loss 0.10956018 - samples/sec: 107.44 - lr: 0.100000 |
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2022-11-06 21:45:50,459 epoch 62 - iter 266/386 - loss 0.11019035 - samples/sec: 106.91 - lr: 0.100000 |
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2022-11-06 21:45:56,323 epoch 62 - iter 304/386 - loss 0.11093248 - samples/sec: 103.73 - lr: 0.100000 |
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2022-11-06 21:46:01,923 epoch 62 - iter 342/386 - loss 0.11064050 - samples/sec: 108.64 - lr: 0.100000 |
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2022-11-06 21:46:07,180 epoch 62 - iter 380/386 - loss 0.11057009 - samples/sec: 115.72 - lr: 0.100000 |
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2022-11-06 21:46:08,019 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:46:08,019 EPOCH 62 done: loss 0.1102 - lr 0.100000 |
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2022-11-06 21:46:17,339 Evaluating as a multi-label problem: False |
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2022-11-06 21:46:17,453 TEST : loss 0.07879139482975006 - f1-score (micro avg) 0.9781 |
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2022-11-06 21:46:17,565 Epoch 62: reducing learning rate of group 0 to 5.0000e-02. |
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2022-11-06 21:46:17,565 BAD EPOCHS (no improvement): 4 |
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2022-11-06 21:46:17,766 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:46:22,757 epoch 63 - iter 38/386 - loss 0.10658703 - samples/sec: 121.93 - lr: 0.050000 |
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2022-11-06 21:46:27,969 epoch 63 - iter 76/386 - loss 0.09978209 - samples/sec: 116.72 - lr: 0.050000 |
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2022-11-06 21:46:33,517 epoch 63 - iter 114/386 - loss 0.10149720 - samples/sec: 109.64 - lr: 0.050000 |
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2022-11-06 21:46:39,162 epoch 63 - iter 152/386 - loss 0.10215730 - samples/sec: 107.77 - lr: 0.050000 |
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2022-11-06 21:46:44,390 epoch 63 - iter 190/386 - loss 0.10305351 - samples/sec: 116.35 - lr: 0.050000 |
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2022-11-06 21:46:50,527 epoch 63 - iter 228/386 - loss 0.10224865 - samples/sec: 99.11 - lr: 0.050000 |
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2022-11-06 21:46:56,167 epoch 63 - iter 266/386 - loss 0.10338093 - samples/sec: 107.87 - lr: 0.050000 |
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2022-11-06 21:47:02,026 epoch 63 - iter 304/386 - loss 0.10281964 - samples/sec: 103.82 - lr: 0.050000 |
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2022-11-06 21:47:07,641 epoch 63 - iter 342/386 - loss 0.10326028 - samples/sec: 108.34 - lr: 0.050000 |
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2022-11-06 21:47:13,252 epoch 63 - iter 380/386 - loss 0.10281205 - samples/sec: 108.42 - lr: 0.050000 |
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2022-11-06 21:47:14,056 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:47:14,056 EPOCH 63 done: loss 0.1023 - lr 0.050000 |
|
2022-11-06 21:47:23,528 Evaluating as a multi-label problem: False |
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2022-11-06 21:47:23,642 TEST : loss 0.07534310221672058 - f1-score (micro avg) 0.9785 |
|
2022-11-06 21:47:23,755 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:47:23,957 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:47:29,857 epoch 64 - iter 38/386 - loss 0.09442249 - samples/sec: 103.14 - lr: 0.050000 |
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2022-11-06 21:47:35,255 epoch 64 - iter 76/386 - loss 0.09624885 - samples/sec: 112.69 - lr: 0.050000 |
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2022-11-06 21:47:40,478 epoch 64 - iter 114/386 - loss 0.09654897 - samples/sec: 116.46 - lr: 0.050000 |
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2022-11-06 21:47:46,285 epoch 64 - iter 152/386 - loss 0.09732478 - samples/sec: 104.76 - lr: 0.050000 |
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2022-11-06 21:47:51,986 epoch 64 - iter 190/386 - loss 0.09745275 - samples/sec: 106.70 - lr: 0.050000 |
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2022-11-06 21:47:57,364 epoch 64 - iter 228/386 - loss 0.09955387 - samples/sec: 113.11 - lr: 0.050000 |
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2022-11-06 21:48:02,959 epoch 64 - iter 266/386 - loss 0.10073669 - samples/sec: 108.74 - lr: 0.050000 |
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2022-11-06 21:48:08,329 epoch 64 - iter 304/386 - loss 0.10014693 - samples/sec: 113.27 - lr: 0.050000 |
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2022-11-06 21:48:13,610 epoch 64 - iter 342/386 - loss 0.09955591 - samples/sec: 115.19 - lr: 0.050000 |
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2022-11-06 21:48:19,482 epoch 64 - iter 380/386 - loss 0.10003809 - samples/sec: 103.60 - lr: 0.050000 |
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2022-11-06 21:48:20,306 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:48:20,306 EPOCH 64 done: loss 0.1000 - lr 0.050000 |
|
2022-11-06 21:48:29,824 Evaluating as a multi-label problem: False |
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2022-11-06 21:48:29,939 TEST : loss 0.07464543730020523 - f1-score (micro avg) 0.9787 |
|
2022-11-06 21:48:30,052 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:48:30,265 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:48:36,046 epoch 65 - iter 38/386 - loss 0.09887412 - samples/sec: 105.25 - lr: 0.050000 |
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2022-11-06 21:48:41,537 epoch 65 - iter 76/386 - loss 0.10023593 - samples/sec: 110.80 - lr: 0.050000 |
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2022-11-06 21:48:47,002 epoch 65 - iter 114/386 - loss 0.09668348 - samples/sec: 111.31 - lr: 0.050000 |
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2022-11-06 21:48:52,703 epoch 65 - iter 152/386 - loss 0.09943600 - samples/sec: 106.71 - lr: 0.050000 |
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2022-11-06 21:48:57,968 epoch 65 - iter 190/386 - loss 0.09869457 - samples/sec: 115.55 - lr: 0.050000 |
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2022-11-06 21:49:03,341 epoch 65 - iter 228/386 - loss 0.09852745 - samples/sec: 113.21 - lr: 0.050000 |
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2022-11-06 21:49:08,708 epoch 65 - iter 266/386 - loss 0.09876531 - samples/sec: 113.37 - lr: 0.050000 |
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2022-11-06 21:49:14,273 epoch 65 - iter 304/386 - loss 0.09762860 - samples/sec: 109.29 - lr: 0.050000 |
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2022-11-06 21:49:19,749 epoch 65 - iter 342/386 - loss 0.09794980 - samples/sec: 111.10 - lr: 0.050000 |
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2022-11-06 21:49:25,372 epoch 65 - iter 380/386 - loss 0.09788718 - samples/sec: 108.17 - lr: 0.050000 |
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2022-11-06 21:49:26,241 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:49:26,242 EPOCH 65 done: loss 0.0977 - lr 0.050000 |
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2022-11-06 21:49:35,664 Evaluating as a multi-label problem: False |
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2022-11-06 21:49:35,779 TEST : loss 0.0754692405462265 - f1-score (micro avg) 0.9788 |
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2022-11-06 21:49:35,891 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:49:36,102 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:49:41,628 epoch 66 - iter 38/386 - loss 0.10147858 - samples/sec: 110.11 - lr: 0.050000 |
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2022-11-06 21:49:47,280 epoch 66 - iter 76/386 - loss 0.10001964 - samples/sec: 107.63 - lr: 0.050000 |
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2022-11-06 21:49:52,958 epoch 66 - iter 114/386 - loss 0.09909022 - samples/sec: 107.14 - lr: 0.050000 |
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2022-11-06 21:49:58,085 epoch 66 - iter 152/386 - loss 0.09947914 - samples/sec: 118.65 - lr: 0.050000 |
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2022-11-06 21:50:03,139 epoch 66 - iter 190/386 - loss 0.09872543 - samples/sec: 120.39 - lr: 0.050000 |
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2022-11-06 21:50:09,214 epoch 66 - iter 228/386 - loss 0.09837586 - samples/sec: 100.13 - lr: 0.050000 |
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2022-11-06 21:50:14,663 epoch 66 - iter 266/386 - loss 0.09818549 - samples/sec: 111.64 - lr: 0.050000 |
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2022-11-06 21:50:20,201 epoch 66 - iter 304/386 - loss 0.09828617 - samples/sec: 109.85 - lr: 0.050000 |
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2022-11-06 21:50:25,865 epoch 66 - iter 342/386 - loss 0.09844885 - samples/sec: 107.40 - lr: 0.050000 |
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2022-11-06 21:50:31,143 epoch 66 - iter 380/386 - loss 0.09810462 - samples/sec: 115.26 - lr: 0.050000 |
|
2022-11-06 21:50:32,093 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:50:32,093 EPOCH 66 done: loss 0.0985 - lr 0.050000 |
|
2022-11-06 21:50:44,000 Evaluating as a multi-label problem: False |
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2022-11-06 21:50:44,114 TEST : loss 0.07432317733764648 - f1-score (micro avg) 0.9786 |
|
2022-11-06 21:50:44,226 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 21:50:44,434 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:50:50,060 epoch 67 - iter 38/386 - loss 0.09547788 - samples/sec: 108.15 - lr: 0.050000 |
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2022-11-06 21:50:55,291 epoch 67 - iter 76/386 - loss 0.09522140 - samples/sec: 116.30 - lr: 0.050000 |
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2022-11-06 21:51:00,893 epoch 67 - iter 114/386 - loss 0.09466178 - samples/sec: 108.59 - lr: 0.050000 |
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2022-11-06 21:51:06,833 epoch 67 - iter 152/386 - loss 0.09304239 - samples/sec: 102.40 - lr: 0.050000 |
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2022-11-06 21:51:12,028 epoch 67 - iter 190/386 - loss 0.09333640 - samples/sec: 117.11 - lr: 0.050000 |
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2022-11-06 21:51:17,096 epoch 67 - iter 228/386 - loss 0.09409673 - samples/sec: 120.04 - lr: 0.050000 |
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2022-11-06 21:51:22,697 epoch 67 - iter 266/386 - loss 0.09443416 - samples/sec: 108.62 - lr: 0.050000 |
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2022-11-06 21:51:28,403 epoch 67 - iter 304/386 - loss 0.09389862 - samples/sec: 106.60 - lr: 0.050000 |
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2022-11-06 21:51:34,208 epoch 67 - iter 342/386 - loss 0.09431186 - samples/sec: 105.56 - lr: 0.050000 |
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2022-11-06 21:51:39,915 epoch 67 - iter 380/386 - loss 0.09465824 - samples/sec: 106.59 - lr: 0.050000 |
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2022-11-06 21:51:40,804 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:51:40,805 EPOCH 67 done: loss 0.0947 - lr 0.050000 |
|
2022-11-06 21:51:50,263 Evaluating as a multi-label problem: False |
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2022-11-06 21:51:50,378 TEST : loss 0.07349660992622375 - f1-score (micro avg) 0.9798 |
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2022-11-06 21:51:50,492 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:51:50,702 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:51:56,209 epoch 68 - iter 38/386 - loss 0.09137315 - samples/sec: 110.51 - lr: 0.050000 |
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2022-11-06 21:52:01,826 epoch 68 - iter 76/386 - loss 0.09330429 - samples/sec: 108.30 - lr: 0.050000 |
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2022-11-06 21:52:07,193 epoch 68 - iter 114/386 - loss 0.09387846 - samples/sec: 113.35 - lr: 0.050000 |
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2022-11-06 21:52:12,840 epoch 68 - iter 152/386 - loss 0.09271632 - samples/sec: 107.72 - lr: 0.050000 |
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2022-11-06 21:52:18,316 epoch 68 - iter 190/386 - loss 0.09315752 - samples/sec: 111.09 - lr: 0.050000 |
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2022-11-06 21:52:23,742 epoch 68 - iter 228/386 - loss 0.09312014 - samples/sec: 112.13 - lr: 0.050000 |
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2022-11-06 21:52:28,716 epoch 68 - iter 266/386 - loss 0.09332579 - samples/sec: 122.31 - lr: 0.050000 |
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2022-11-06 21:52:34,044 epoch 68 - iter 304/386 - loss 0.09372537 - samples/sec: 114.16 - lr: 0.050000 |
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2022-11-06 21:52:39,864 epoch 68 - iter 342/386 - loss 0.09456013 - samples/sec: 104.54 - lr: 0.050000 |
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2022-11-06 21:52:45,686 epoch 68 - iter 380/386 - loss 0.09506871 - samples/sec: 104.47 - lr: 0.050000 |
|
2022-11-06 21:52:46,446 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:52:46,446 EPOCH 68 done: loss 0.0954 - lr 0.050000 |
|
2022-11-06 21:52:55,924 Evaluating as a multi-label problem: False |
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2022-11-06 21:52:56,039 TEST : loss 0.07435259222984314 - f1-score (micro avg) 0.9791 |
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2022-11-06 21:52:56,152 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 21:52:56,363 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:53:01,852 epoch 69 - iter 38/386 - loss 0.09120895 - samples/sec: 110.84 - lr: 0.050000 |
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2022-11-06 21:53:07,266 epoch 69 - iter 76/386 - loss 0.09158650 - samples/sec: 112.38 - lr: 0.050000 |
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2022-11-06 21:53:13,000 epoch 69 - iter 114/386 - loss 0.09354837 - samples/sec: 106.09 - lr: 0.050000 |
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2022-11-06 21:53:18,752 epoch 69 - iter 152/386 - loss 0.09241557 - samples/sec: 106.54 - lr: 0.050000 |
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2022-11-06 21:53:24,432 epoch 69 - iter 190/386 - loss 0.09405392 - samples/sec: 107.10 - lr: 0.050000 |
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2022-11-06 21:53:29,942 epoch 69 - iter 228/386 - loss 0.09437177 - samples/sec: 110.42 - lr: 0.050000 |
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2022-11-06 21:53:35,360 epoch 69 - iter 266/386 - loss 0.09345038 - samples/sec: 112.28 - lr: 0.050000 |
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2022-11-06 21:53:40,749 epoch 69 - iter 304/386 - loss 0.09349443 - samples/sec: 112.88 - lr: 0.050000 |
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2022-11-06 21:53:46,313 epoch 69 - iter 342/386 - loss 0.09350680 - samples/sec: 109.33 - lr: 0.050000 |
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2022-11-06 21:53:51,756 epoch 69 - iter 380/386 - loss 0.09377817 - samples/sec: 111.77 - lr: 0.050000 |
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2022-11-06 21:53:52,543 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:53:52,543 EPOCH 69 done: loss 0.0937 - lr 0.050000 |
|
2022-11-06 21:54:02,057 Evaluating as a multi-label problem: False |
|
2022-11-06 21:54:02,171 TEST : loss 0.0757945254445076 - f1-score (micro avg) 0.9784 |
|
2022-11-06 21:54:02,284 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:54:02,486 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:54:08,097 epoch 70 - iter 38/386 - loss 0.08890860 - samples/sec: 108.45 - lr: 0.050000 |
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2022-11-06 21:54:13,612 epoch 70 - iter 76/386 - loss 0.09276883 - samples/sec: 110.30 - lr: 0.050000 |
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2022-11-06 21:54:19,103 epoch 70 - iter 114/386 - loss 0.09169168 - samples/sec: 110.78 - lr: 0.050000 |
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2022-11-06 21:54:24,503 epoch 70 - iter 152/386 - loss 0.09332129 - samples/sec: 112.65 - lr: 0.050000 |
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2022-11-06 21:54:30,183 epoch 70 - iter 190/386 - loss 0.09109459 - samples/sec: 107.10 - lr: 0.050000 |
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2022-11-06 21:54:35,735 epoch 70 - iter 228/386 - loss 0.09359296 - samples/sec: 109.56 - lr: 0.050000 |
|
2022-11-06 21:54:41,443 epoch 70 - iter 266/386 - loss 0.09350137 - samples/sec: 106.59 - lr: 0.050000 |
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2022-11-06 21:54:46,719 epoch 70 - iter 304/386 - loss 0.09343522 - samples/sec: 115.31 - lr: 0.050000 |
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2022-11-06 21:54:52,170 epoch 70 - iter 342/386 - loss 0.09365079 - samples/sec: 111.59 - lr: 0.050000 |
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2022-11-06 21:54:57,826 epoch 70 - iter 380/386 - loss 0.09379290 - samples/sec: 107.55 - lr: 0.050000 |
|
2022-11-06 21:54:58,474 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:54:58,474 EPOCH 70 done: loss 0.0937 - lr 0.050000 |
|
2022-11-06 21:55:07,791 Evaluating as a multi-label problem: False |
|
2022-11-06 21:55:07,905 TEST : loss 0.0764009952545166 - f1-score (micro avg) 0.9789 |
|
2022-11-06 21:55:08,017 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:55:08,221 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:55:13,770 epoch 71 - iter 38/386 - loss 0.08554802 - samples/sec: 109.64 - lr: 0.050000 |
|
2022-11-06 21:55:19,301 epoch 71 - iter 76/386 - loss 0.09025236 - samples/sec: 110.00 - lr: 0.050000 |
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2022-11-06 21:55:25,041 epoch 71 - iter 114/386 - loss 0.09217128 - samples/sec: 105.97 - lr: 0.050000 |
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2022-11-06 21:55:30,809 epoch 71 - iter 152/386 - loss 0.09300167 - samples/sec: 105.47 - lr: 0.050000 |
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2022-11-06 21:55:36,154 epoch 71 - iter 190/386 - loss 0.09282890 - samples/sec: 113.80 - lr: 0.050000 |
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2022-11-06 21:55:41,243 epoch 71 - iter 228/386 - loss 0.09400901 - samples/sec: 119.54 - lr: 0.050000 |
|
2022-11-06 21:55:46,720 epoch 71 - iter 266/386 - loss 0.09346036 - samples/sec: 111.93 - lr: 0.050000 |
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2022-11-06 21:55:52,245 epoch 71 - iter 304/386 - loss 0.09346459 - samples/sec: 110.11 - lr: 0.050000 |
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2022-11-06 21:55:58,282 epoch 71 - iter 342/386 - loss 0.09398476 - samples/sec: 100.75 - lr: 0.050000 |
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2022-11-06 21:56:03,625 epoch 71 - iter 380/386 - loss 0.09421206 - samples/sec: 113.87 - lr: 0.050000 |
|
2022-11-06 21:56:04,435 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:56:04,435 EPOCH 71 done: loss 0.0942 - lr 0.050000 |
|
2022-11-06 21:56:13,395 Evaluating as a multi-label problem: False |
|
2022-11-06 21:56:13,509 TEST : loss 0.07746423035860062 - f1-score (micro avg) 0.9776 |
|
2022-11-06 21:56:13,620 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 21:56:13,824 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 21:56:19,279 epoch 72 - iter 38/386 - loss 0.08836120 - samples/sec: 111.56 - lr: 0.050000 |
|
2022-11-06 21:56:25,113 epoch 72 - iter 76/386 - loss 0.09152661 - samples/sec: 104.27 - lr: 0.050000 |
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2022-11-06 21:56:30,762 epoch 72 - iter 114/386 - loss 0.09266384 - samples/sec: 107.67 - lr: 0.050000 |
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2022-11-06 21:56:36,310 epoch 72 - iter 152/386 - loss 0.09210641 - samples/sec: 109.66 - lr: 0.050000 |
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2022-11-06 21:56:41,389 epoch 72 - iter 190/386 - loss 0.09198951 - samples/sec: 119.76 - lr: 0.050000 |
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2022-11-06 21:56:46,984 epoch 72 - iter 228/386 - loss 0.09362383 - samples/sec: 108.73 - lr: 0.050000 |
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2022-11-06 21:56:52,622 epoch 72 - iter 266/386 - loss 0.09271150 - samples/sec: 107.89 - lr: 0.050000 |
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2022-11-06 21:56:58,105 epoch 72 - iter 304/386 - loss 0.09327678 - samples/sec: 110.95 - lr: 0.050000 |
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2022-11-06 21:57:03,413 epoch 72 - iter 342/386 - loss 0.09330768 - samples/sec: 114.62 - lr: 0.050000 |
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2022-11-06 21:57:09,064 epoch 72 - iter 380/386 - loss 0.09305626 - samples/sec: 107.65 - lr: 0.050000 |
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2022-11-06 21:57:09,872 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:57:09,872 EPOCH 72 done: loss 0.0932 - lr 0.050000 |
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2022-11-06 21:57:18,688 Evaluating as a multi-label problem: False |
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2022-11-06 21:57:18,802 TEST : loss 0.07610904425382614 - f1-score (micro avg) 0.9783 |
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2022-11-06 21:57:18,912 BAD EPOCHS (no improvement): 0 |
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2022-11-06 21:57:19,120 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:57:24,632 epoch 73 - iter 38/386 - loss 0.08300037 - samples/sec: 110.39 - lr: 0.050000 |
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2022-11-06 21:57:30,262 epoch 73 - iter 76/386 - loss 0.08575533 - samples/sec: 108.06 - lr: 0.050000 |
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2022-11-06 21:57:35,831 epoch 73 - iter 114/386 - loss 0.08793053 - samples/sec: 109.98 - lr: 0.050000 |
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2022-11-06 21:57:41,583 epoch 73 - iter 152/386 - loss 0.09031249 - samples/sec: 105.76 - lr: 0.050000 |
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2022-11-06 21:57:47,239 epoch 73 - iter 190/386 - loss 0.09171636 - samples/sec: 107.55 - lr: 0.050000 |
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2022-11-06 21:57:52,452 epoch 73 - iter 228/386 - loss 0.09110892 - samples/sec: 117.66 - lr: 0.050000 |
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2022-11-06 21:57:58,120 epoch 73 - iter 266/386 - loss 0.09069697 - samples/sec: 107.33 - lr: 0.050000 |
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2022-11-06 21:58:03,045 epoch 73 - iter 304/386 - loss 0.09137763 - samples/sec: 123.52 - lr: 0.050000 |
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2022-11-06 21:58:08,421 epoch 73 - iter 342/386 - loss 0.09163594 - samples/sec: 113.15 - lr: 0.050000 |
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2022-11-06 21:58:14,624 epoch 73 - iter 380/386 - loss 0.09233790 - samples/sec: 98.07 - lr: 0.050000 |
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2022-11-06 21:58:15,352 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:58:15,352 EPOCH 73 done: loss 0.0927 - lr 0.050000 |
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2022-11-06 21:58:24,784 Evaluating as a multi-label problem: False |
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2022-11-06 21:58:24,897 TEST : loss 0.07682343572378159 - f1-score (micro avg) 0.9791 |
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2022-11-06 21:58:25,009 BAD EPOCHS (no improvement): 0 |
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2022-11-06 21:58:25,213 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:58:30,702 epoch 74 - iter 38/386 - loss 0.09071120 - samples/sec: 110.85 - lr: 0.050000 |
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2022-11-06 21:58:36,204 epoch 74 - iter 76/386 - loss 0.09116074 - samples/sec: 110.56 - lr: 0.050000 |
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2022-11-06 21:58:41,481 epoch 74 - iter 114/386 - loss 0.09187654 - samples/sec: 115.28 - lr: 0.050000 |
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2022-11-06 21:58:46,655 epoch 74 - iter 152/386 - loss 0.09141319 - samples/sec: 117.58 - lr: 0.050000 |
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2022-11-06 21:58:52,078 epoch 74 - iter 190/386 - loss 0.09142797 - samples/sec: 112.17 - lr: 0.050000 |
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2022-11-06 21:58:57,689 epoch 74 - iter 228/386 - loss 0.08984326 - samples/sec: 108.42 - lr: 0.050000 |
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2022-11-06 21:59:03,721 epoch 74 - iter 266/386 - loss 0.08897908 - samples/sec: 100.84 - lr: 0.050000 |
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2022-11-06 21:59:08,915 epoch 74 - iter 304/386 - loss 0.08840306 - samples/sec: 117.13 - lr: 0.050000 |
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2022-11-06 21:59:14,226 epoch 74 - iter 342/386 - loss 0.08851215 - samples/sec: 114.55 - lr: 0.050000 |
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2022-11-06 21:59:19,603 epoch 74 - iter 380/386 - loss 0.08856454 - samples/sec: 113.13 - lr: 0.050000 |
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2022-11-06 21:59:20,499 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:59:20,499 EPOCH 74 done: loss 0.0887 - lr 0.050000 |
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2022-11-06 21:59:29,816 Evaluating as a multi-label problem: False |
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2022-11-06 21:59:29,929 TEST : loss 0.07699835300445557 - f1-score (micro avg) 0.9795 |
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2022-11-06 21:59:30,041 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 21:59:30,248 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 21:59:35,938 epoch 75 - iter 38/386 - loss 0.09010983 - samples/sec: 106.93 - lr: 0.050000 |
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2022-11-06 21:59:41,512 epoch 75 - iter 76/386 - loss 0.08888721 - samples/sec: 109.14 - lr: 0.050000 |
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2022-11-06 21:59:46,674 epoch 75 - iter 114/386 - loss 0.08627651 - samples/sec: 117.85 - lr: 0.050000 |
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2022-11-06 21:59:51,815 epoch 75 - iter 152/386 - loss 0.08648960 - samples/sec: 118.34 - lr: 0.050000 |
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2022-11-06 21:59:57,162 epoch 75 - iter 190/386 - loss 0.08750875 - samples/sec: 113.77 - lr: 0.050000 |
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2022-11-06 22:00:02,844 epoch 75 - iter 228/386 - loss 0.08733463 - samples/sec: 107.06 - lr: 0.050000 |
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2022-11-06 22:00:08,984 epoch 75 - iter 266/386 - loss 0.08776781 - samples/sec: 99.07 - lr: 0.050000 |
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2022-11-06 22:00:14,611 epoch 75 - iter 304/386 - loss 0.08859041 - samples/sec: 108.11 - lr: 0.050000 |
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2022-11-06 22:00:19,915 epoch 75 - iter 342/386 - loss 0.09008267 - samples/sec: 114.70 - lr: 0.050000 |
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2022-11-06 22:00:25,381 epoch 75 - iter 380/386 - loss 0.09035732 - samples/sec: 111.29 - lr: 0.050000 |
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2022-11-06 22:00:26,276 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:00:26,277 EPOCH 75 done: loss 0.0905 - lr 0.050000 |
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2022-11-06 22:00:35,742 Evaluating as a multi-label problem: False |
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2022-11-06 22:00:35,857 TEST : loss 0.07650885730981827 - f1-score (micro avg) 0.9794 |
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2022-11-06 22:00:35,969 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 22:00:36,169 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:00:41,371 epoch 76 - iter 38/386 - loss 0.08535642 - samples/sec: 116.98 - lr: 0.050000 |
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2022-11-06 22:00:46,936 epoch 76 - iter 76/386 - loss 0.08909989 - samples/sec: 109.30 - lr: 0.050000 |
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2022-11-06 22:00:52,273 epoch 76 - iter 114/386 - loss 0.08858041 - samples/sec: 114.00 - lr: 0.050000 |
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2022-11-06 22:00:57,019 epoch 76 - iter 152/386 - loss 0.09111687 - samples/sec: 128.16 - lr: 0.050000 |
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2022-11-06 22:01:01,932 epoch 76 - iter 190/386 - loss 0.09184363 - samples/sec: 123.84 - lr: 0.050000 |
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2022-11-06 22:01:07,359 epoch 76 - iter 228/386 - loss 0.09209636 - samples/sec: 112.10 - lr: 0.050000 |
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2022-11-06 22:01:12,927 epoch 76 - iter 266/386 - loss 0.09302243 - samples/sec: 109.24 - lr: 0.050000 |
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2022-11-06 22:01:18,650 epoch 76 - iter 304/386 - loss 0.09212630 - samples/sec: 106.30 - lr: 0.050000 |
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2022-11-06 22:01:24,682 epoch 76 - iter 342/386 - loss 0.09211552 - samples/sec: 100.85 - lr: 0.050000 |
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2022-11-06 22:01:30,494 epoch 76 - iter 380/386 - loss 0.09221232 - samples/sec: 104.67 - lr: 0.050000 |
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2022-11-06 22:01:31,413 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:01:31,413 EPOCH 76 done: loss 0.0920 - lr 0.050000 |
|
2022-11-06 22:01:43,220 Evaluating as a multi-label problem: False |
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2022-11-06 22:01:43,334 TEST : loss 0.07444333285093307 - f1-score (micro avg) 0.9793 |
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2022-11-06 22:01:43,445 BAD EPOCHS (no improvement): 2 |
|
2022-11-06 22:01:43,657 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:01:49,340 epoch 77 - iter 38/386 - loss 0.08895759 - samples/sec: 107.07 - lr: 0.050000 |
|
2022-11-06 22:01:54,722 epoch 77 - iter 76/386 - loss 0.08888293 - samples/sec: 113.03 - lr: 0.050000 |
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2022-11-06 22:02:00,637 epoch 77 - iter 114/386 - loss 0.09145351 - samples/sec: 102.84 - lr: 0.050000 |
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2022-11-06 22:02:05,857 epoch 77 - iter 152/386 - loss 0.09274616 - samples/sec: 116.55 - lr: 0.050000 |
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2022-11-06 22:02:10,767 epoch 77 - iter 190/386 - loss 0.09381220 - samples/sec: 123.90 - lr: 0.050000 |
|
2022-11-06 22:02:16,246 epoch 77 - iter 228/386 - loss 0.09315648 - samples/sec: 111.03 - lr: 0.050000 |
|
2022-11-06 22:02:21,442 epoch 77 - iter 266/386 - loss 0.09256458 - samples/sec: 118.03 - lr: 0.050000 |
|
2022-11-06 22:02:27,103 epoch 77 - iter 304/386 - loss 0.09210060 - samples/sec: 107.46 - lr: 0.050000 |
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2022-11-06 22:02:32,763 epoch 77 - iter 342/386 - loss 0.09166523 - samples/sec: 107.48 - lr: 0.050000 |
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2022-11-06 22:02:38,387 epoch 77 - iter 380/386 - loss 0.09144354 - samples/sec: 108.15 - lr: 0.050000 |
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2022-11-06 22:02:39,265 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:02:39,266 EPOCH 77 done: loss 0.0915 - lr 0.050000 |
|
2022-11-06 22:02:48,671 Evaluating as a multi-label problem: False |
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2022-11-06 22:02:48,785 TEST : loss 0.07569604367017746 - f1-score (micro avg) 0.9792 |
|
2022-11-06 22:02:48,897 BAD EPOCHS (no improvement): 3 |
|
2022-11-06 22:02:49,105 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:02:54,891 epoch 78 - iter 38/386 - loss 0.08376892 - samples/sec: 105.17 - lr: 0.050000 |
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2022-11-06 22:03:00,207 epoch 78 - iter 76/386 - loss 0.08734464 - samples/sec: 114.43 - lr: 0.050000 |
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2022-11-06 22:03:05,970 epoch 78 - iter 114/386 - loss 0.08772487 - samples/sec: 105.54 - lr: 0.050000 |
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2022-11-06 22:03:11,595 epoch 78 - iter 152/386 - loss 0.08741174 - samples/sec: 108.15 - lr: 0.050000 |
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2022-11-06 22:03:17,144 epoch 78 - iter 190/386 - loss 0.08621154 - samples/sec: 109.62 - lr: 0.050000 |
|
2022-11-06 22:03:22,343 epoch 78 - iter 228/386 - loss 0.08552517 - samples/sec: 117.01 - lr: 0.050000 |
|
2022-11-06 22:03:27,433 epoch 78 - iter 266/386 - loss 0.08659634 - samples/sec: 119.53 - lr: 0.050000 |
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2022-11-06 22:03:32,676 epoch 78 - iter 304/386 - loss 0.08698140 - samples/sec: 116.03 - lr: 0.050000 |
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2022-11-06 22:03:38,658 epoch 78 - iter 342/386 - loss 0.08706887 - samples/sec: 101.69 - lr: 0.050000 |
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2022-11-06 22:03:44,138 epoch 78 - iter 380/386 - loss 0.08741793 - samples/sec: 111.00 - lr: 0.050000 |
|
2022-11-06 22:03:44,857 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:03:44,857 EPOCH 78 done: loss 0.0875 - lr 0.050000 |
|
2022-11-06 22:03:54,244 Evaluating as a multi-label problem: False |
|
2022-11-06 22:03:54,358 TEST : loss 0.07991818338632584 - f1-score (micro avg) 0.9787 |
|
2022-11-06 22:03:54,471 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 22:03:54,685 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:03:59,993 epoch 79 - iter 38/386 - loss 0.08928639 - samples/sec: 114.62 - lr: 0.050000 |
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2022-11-06 22:04:05,218 epoch 79 - iter 76/386 - loss 0.08696352 - samples/sec: 116.44 - lr: 0.050000 |
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2022-11-06 22:04:10,821 epoch 79 - iter 114/386 - loss 0.08802286 - samples/sec: 108.57 - lr: 0.050000 |
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2022-11-06 22:04:16,869 epoch 79 - iter 152/386 - loss 0.08901779 - samples/sec: 100.58 - lr: 0.050000 |
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2022-11-06 22:04:22,263 epoch 79 - iter 190/386 - loss 0.08795694 - samples/sec: 112.78 - lr: 0.050000 |
|
2022-11-06 22:04:27,565 epoch 79 - iter 228/386 - loss 0.08824170 - samples/sec: 114.73 - lr: 0.050000 |
|
2022-11-06 22:04:32,608 epoch 79 - iter 266/386 - loss 0.08800000 - samples/sec: 120.63 - lr: 0.050000 |
|
2022-11-06 22:04:37,722 epoch 79 - iter 304/386 - loss 0.08685455 - samples/sec: 118.97 - lr: 0.050000 |
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2022-11-06 22:04:43,314 epoch 79 - iter 342/386 - loss 0.08722570 - samples/sec: 108.77 - lr: 0.050000 |
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2022-11-06 22:04:49,093 epoch 79 - iter 380/386 - loss 0.08745041 - samples/sec: 105.27 - lr: 0.050000 |
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2022-11-06 22:04:50,042 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:04:50,042 EPOCH 79 done: loss 0.0875 - lr 0.050000 |
|
2022-11-06 22:04:59,310 Evaluating as a multi-label problem: False |
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2022-11-06 22:04:59,424 TEST : loss 0.07551249861717224 - f1-score (micro avg) 0.9797 |
|
2022-11-06 22:04:59,535 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 22:04:59,744 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:05:04,922 epoch 80 - iter 38/386 - loss 0.09880198 - samples/sec: 117.52 - lr: 0.050000 |
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2022-11-06 22:05:11,034 epoch 80 - iter 76/386 - loss 0.09604834 - samples/sec: 99.52 - lr: 0.050000 |
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2022-11-06 22:05:16,842 epoch 80 - iter 114/386 - loss 0.09443440 - samples/sec: 104.74 - lr: 0.050000 |
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2022-11-06 22:05:22,343 epoch 80 - iter 152/386 - loss 0.09369188 - samples/sec: 110.59 - lr: 0.050000 |
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2022-11-06 22:05:27,484 epoch 80 - iter 190/386 - loss 0.09212382 - samples/sec: 118.33 - lr: 0.050000 |
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2022-11-06 22:05:32,960 epoch 80 - iter 228/386 - loss 0.09101292 - samples/sec: 111.09 - lr: 0.050000 |
|
2022-11-06 22:05:38,305 epoch 80 - iter 266/386 - loss 0.09099899 - samples/sec: 113.82 - lr: 0.050000 |
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2022-11-06 22:05:44,025 epoch 80 - iter 304/386 - loss 0.09116268 - samples/sec: 106.36 - lr: 0.050000 |
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2022-11-06 22:05:49,444 epoch 80 - iter 342/386 - loss 0.09095614 - samples/sec: 112.25 - lr: 0.050000 |
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2022-11-06 22:05:54,693 epoch 80 - iter 380/386 - loss 0.09117192 - samples/sec: 115.91 - lr: 0.050000 |
|
2022-11-06 22:05:55,455 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:05:55,455 EPOCH 80 done: loss 0.0910 - lr 0.050000 |
|
2022-11-06 22:06:04,822 Evaluating as a multi-label problem: False |
|
2022-11-06 22:06:04,939 TEST : loss 0.07765697687864304 - f1-score (micro avg) 0.9791 |
|
2022-11-06 22:06:05,051 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 22:06:05,262 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:06:10,885 epoch 81 - iter 38/386 - loss 0.08081290 - samples/sec: 108.20 - lr: 0.050000 |
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2022-11-06 22:06:16,437 epoch 81 - iter 76/386 - loss 0.08337375 - samples/sec: 109.57 - lr: 0.050000 |
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2022-11-06 22:06:22,013 epoch 81 - iter 114/386 - loss 0.08302250 - samples/sec: 109.10 - lr: 0.050000 |
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2022-11-06 22:06:27,395 epoch 81 - iter 152/386 - loss 0.08480407 - samples/sec: 113.93 - lr: 0.050000 |
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2022-11-06 22:06:33,387 epoch 81 - iter 190/386 - loss 0.08609702 - samples/sec: 101.51 - lr: 0.050000 |
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2022-11-06 22:06:39,214 epoch 81 - iter 228/386 - loss 0.08554252 - samples/sec: 104.41 - lr: 0.050000 |
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2022-11-06 22:06:44,743 epoch 81 - iter 266/386 - loss 0.08462515 - samples/sec: 110.01 - lr: 0.050000 |
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2022-11-06 22:06:50,380 epoch 81 - iter 304/386 - loss 0.08538954 - samples/sec: 107.91 - lr: 0.050000 |
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2022-11-06 22:06:55,651 epoch 81 - iter 342/386 - loss 0.08586110 - samples/sec: 115.41 - lr: 0.050000 |
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2022-11-06 22:07:00,762 epoch 81 - iter 380/386 - loss 0.08543691 - samples/sec: 119.04 - lr: 0.050000 |
|
2022-11-06 22:07:01,391 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:07:01,391 EPOCH 81 done: loss 0.0858 - lr 0.050000 |
|
2022-11-06 22:07:10,242 Evaluating as a multi-label problem: False |
|
2022-11-06 22:07:10,356 TEST : loss 0.07825277745723724 - f1-score (micro avg) 0.9793 |
|
2022-11-06 22:07:10,468 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 22:07:10,670 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:07:16,234 epoch 82 - iter 38/386 - loss 0.08629919 - samples/sec: 109.36 - lr: 0.050000 |
|
2022-11-06 22:07:22,344 epoch 82 - iter 76/386 - loss 0.08451248 - samples/sec: 99.56 - lr: 0.050000 |
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2022-11-06 22:07:28,020 epoch 82 - iter 114/386 - loss 0.08580786 - samples/sec: 107.17 - lr: 0.050000 |
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2022-11-06 22:07:33,590 epoch 82 - iter 152/386 - loss 0.08754692 - samples/sec: 109.21 - lr: 0.050000 |
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2022-11-06 22:07:38,703 epoch 82 - iter 190/386 - loss 0.08805859 - samples/sec: 118.99 - lr: 0.050000 |
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2022-11-06 22:07:44,067 epoch 82 - iter 228/386 - loss 0.08781350 - samples/sec: 113.42 - lr: 0.050000 |
|
2022-11-06 22:07:49,722 epoch 82 - iter 266/386 - loss 0.08812045 - samples/sec: 107.57 - lr: 0.050000 |
|
2022-11-06 22:07:55,087 epoch 82 - iter 304/386 - loss 0.08978244 - samples/sec: 113.38 - lr: 0.050000 |
|
2022-11-06 22:08:00,793 epoch 82 - iter 342/386 - loss 0.08986460 - samples/sec: 106.62 - lr: 0.050000 |
|
2022-11-06 22:08:05,834 epoch 82 - iter 380/386 - loss 0.08970849 - samples/sec: 120.69 - lr: 0.050000 |
|
2022-11-06 22:08:06,579 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:08:06,579 EPOCH 82 done: loss 0.0899 - lr 0.050000 |
|
2022-11-06 22:08:15,556 Evaluating as a multi-label problem: False |
|
2022-11-06 22:08:15,670 TEST : loss 0.077557772397995 - f1-score (micro avg) 0.9795 |
|
2022-11-06 22:08:15,782 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 22:08:15,988 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:08:21,824 epoch 83 - iter 38/386 - loss 0.08818104 - samples/sec: 104.27 - lr: 0.050000 |
|
2022-11-06 22:08:27,128 epoch 83 - iter 76/386 - loss 0.08980860 - samples/sec: 114.68 - lr: 0.050000 |
|
2022-11-06 22:08:32,632 epoch 83 - iter 114/386 - loss 0.08931832 - samples/sec: 110.53 - lr: 0.050000 |
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2022-11-06 22:08:37,949 epoch 83 - iter 152/386 - loss 0.08688520 - samples/sec: 114.43 - lr: 0.050000 |
|
2022-11-06 22:08:43,185 epoch 83 - iter 190/386 - loss 0.08696988 - samples/sec: 116.17 - lr: 0.050000 |
|
2022-11-06 22:08:48,329 epoch 83 - iter 228/386 - loss 0.08623230 - samples/sec: 118.28 - lr: 0.050000 |
|
2022-11-06 22:08:54,180 epoch 83 - iter 266/386 - loss 0.08715665 - samples/sec: 103.96 - lr: 0.050000 |
|
2022-11-06 22:08:59,938 epoch 83 - iter 304/386 - loss 0.08655812 - samples/sec: 105.64 - lr: 0.050000 |
|
2022-11-06 22:09:05,407 epoch 83 - iter 342/386 - loss 0.08648025 - samples/sec: 111.23 - lr: 0.050000 |
|
2022-11-06 22:09:11,416 epoch 83 - iter 380/386 - loss 0.08651596 - samples/sec: 101.25 - lr: 0.050000 |
|
2022-11-06 22:09:12,286 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:09:12,286 EPOCH 83 done: loss 0.0868 - lr 0.050000 |
|
2022-11-06 22:09:21,669 Evaluating as a multi-label problem: False |
|
2022-11-06 22:09:21,783 TEST : loss 0.07837608456611633 - f1-score (micro avg) 0.9794 |
|
2022-11-06 22:09:21,895 BAD EPOCHS (no improvement): 2 |
|
2022-11-06 22:09:22,100 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:09:27,084 epoch 84 - iter 38/386 - loss 0.08085540 - samples/sec: 122.10 - lr: 0.050000 |
|
2022-11-06 22:09:32,394 epoch 84 - iter 76/386 - loss 0.08316482 - samples/sec: 114.55 - lr: 0.050000 |
|
2022-11-06 22:09:37,928 epoch 84 - iter 114/386 - loss 0.08390017 - samples/sec: 109.92 - lr: 0.050000 |
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2022-11-06 22:09:43,188 epoch 84 - iter 152/386 - loss 0.08477912 - samples/sec: 115.65 - lr: 0.050000 |
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2022-11-06 22:09:48,647 epoch 84 - iter 190/386 - loss 0.08779591 - samples/sec: 111.44 - lr: 0.050000 |
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2022-11-06 22:09:54,140 epoch 84 - iter 228/386 - loss 0.08604904 - samples/sec: 110.75 - lr: 0.050000 |
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2022-11-06 22:09:59,696 epoch 84 - iter 266/386 - loss 0.08526498 - samples/sec: 109.50 - lr: 0.050000 |
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2022-11-06 22:10:05,344 epoch 84 - iter 304/386 - loss 0.08543825 - samples/sec: 107.71 - lr: 0.050000 |
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2022-11-06 22:10:11,119 epoch 84 - iter 342/386 - loss 0.08616034 - samples/sec: 105.33 - lr: 0.050000 |
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2022-11-06 22:10:16,300 epoch 84 - iter 380/386 - loss 0.08594080 - samples/sec: 117.42 - lr: 0.050000 |
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2022-11-06 22:10:17,085 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:10:17,085 EPOCH 84 done: loss 0.0859 - lr 0.050000 |
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2022-11-06 22:10:26,482 Evaluating as a multi-label problem: False |
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2022-11-06 22:10:26,595 TEST : loss 0.07908571511507034 - f1-score (micro avg) 0.9791 |
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2022-11-06 22:10:26,707 BAD EPOCHS (no improvement): 3 |
|
2022-11-06 22:10:26,916 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:10:32,295 epoch 85 - iter 38/386 - loss 0.08409247 - samples/sec: 113.11 - lr: 0.050000 |
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2022-11-06 22:10:37,764 epoch 85 - iter 76/386 - loss 0.08732911 - samples/sec: 111.25 - lr: 0.050000 |
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2022-11-06 22:10:42,541 epoch 85 - iter 114/386 - loss 0.08752875 - samples/sec: 127.34 - lr: 0.050000 |
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2022-11-06 22:10:47,789 epoch 85 - iter 152/386 - loss 0.08668668 - samples/sec: 115.92 - lr: 0.050000 |
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2022-11-06 22:10:53,048 epoch 85 - iter 190/386 - loss 0.08746045 - samples/sec: 115.67 - lr: 0.050000 |
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2022-11-06 22:10:58,323 epoch 85 - iter 228/386 - loss 0.08632880 - samples/sec: 115.32 - lr: 0.050000 |
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2022-11-06 22:11:03,801 epoch 85 - iter 266/386 - loss 0.08607122 - samples/sec: 111.06 - lr: 0.050000 |
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2022-11-06 22:11:10,221 epoch 85 - iter 304/386 - loss 0.08680703 - samples/sec: 94.74 - lr: 0.050000 |
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2022-11-06 22:11:15,817 epoch 85 - iter 342/386 - loss 0.08675650 - samples/sec: 108.71 - lr: 0.050000 |
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2022-11-06 22:11:21,365 epoch 85 - iter 380/386 - loss 0.08631388 - samples/sec: 109.66 - lr: 0.050000 |
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2022-11-06 22:11:22,266 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:11:22,267 EPOCH 85 done: loss 0.0860 - lr 0.050000 |
|
2022-11-06 22:11:31,819 Evaluating as a multi-label problem: False |
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2022-11-06 22:11:31,935 TEST : loss 0.07693811506032944 - f1-score (micro avg) 0.9796 |
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2022-11-06 22:11:32,049 Epoch 85: reducing learning rate of group 0 to 2.5000e-02. |
|
2022-11-06 22:11:32,049 BAD EPOCHS (no improvement): 4 |
|
2022-11-06 22:11:32,261 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:11:38,275 epoch 86 - iter 38/386 - loss 0.09401872 - samples/sec: 101.17 - lr: 0.025000 |
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2022-11-06 22:11:43,699 epoch 86 - iter 76/386 - loss 0.09432225 - samples/sec: 112.17 - lr: 0.025000 |
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2022-11-06 22:11:49,718 epoch 86 - iter 114/386 - loss 0.08964112 - samples/sec: 101.77 - lr: 0.025000 |
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2022-11-06 22:11:54,809 epoch 86 - iter 152/386 - loss 0.08763708 - samples/sec: 119.50 - lr: 0.025000 |
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2022-11-06 22:12:00,232 epoch 86 - iter 190/386 - loss 0.08731319 - samples/sec: 112.18 - lr: 0.025000 |
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2022-11-06 22:12:05,644 epoch 86 - iter 228/386 - loss 0.08663491 - samples/sec: 112.41 - lr: 0.025000 |
|
2022-11-06 22:12:11,665 epoch 86 - iter 266/386 - loss 0.08581371 - samples/sec: 101.05 - lr: 0.025000 |
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2022-11-06 22:12:17,252 epoch 86 - iter 304/386 - loss 0.08535848 - samples/sec: 108.88 - lr: 0.025000 |
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2022-11-06 22:12:22,510 epoch 86 - iter 342/386 - loss 0.08557678 - samples/sec: 115.69 - lr: 0.025000 |
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2022-11-06 22:12:28,286 epoch 86 - iter 380/386 - loss 0.08575220 - samples/sec: 105.33 - lr: 0.025000 |
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2022-11-06 22:12:29,093 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:12:29,093 EPOCH 86 done: loss 0.0860 - lr 0.025000 |
|
2022-11-06 22:12:38,762 Evaluating as a multi-label problem: False |
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2022-11-06 22:12:38,878 TEST : loss 0.07507522404193878 - f1-score (micro avg) 0.9797 |
|
2022-11-06 22:12:38,992 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 22:12:39,205 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:12:44,844 epoch 87 - iter 38/386 - loss 0.08439559 - samples/sec: 107.91 - lr: 0.025000 |
|
2022-11-06 22:12:50,265 epoch 87 - iter 76/386 - loss 0.08054664 - samples/sec: 112.21 - lr: 0.025000 |
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2022-11-06 22:12:55,855 epoch 87 - iter 114/386 - loss 0.08111561 - samples/sec: 108.83 - lr: 0.025000 |
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2022-11-06 22:13:01,318 epoch 87 - iter 152/386 - loss 0.08025030 - samples/sec: 111.36 - lr: 0.025000 |
|
2022-11-06 22:13:06,932 epoch 87 - iter 190/386 - loss 0.08014814 - samples/sec: 108.37 - lr: 0.025000 |
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2022-11-06 22:13:12,282 epoch 87 - iter 228/386 - loss 0.07974041 - samples/sec: 113.70 - lr: 0.025000 |
|
2022-11-06 22:13:17,692 epoch 87 - iter 266/386 - loss 0.07913362 - samples/sec: 112.45 - lr: 0.025000 |
|
2022-11-06 22:13:23,418 epoch 87 - iter 304/386 - loss 0.07971830 - samples/sec: 106.25 - lr: 0.025000 |
|
2022-11-06 22:13:28,893 epoch 87 - iter 342/386 - loss 0.08018386 - samples/sec: 111.12 - lr: 0.025000 |
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2022-11-06 22:13:34,703 epoch 87 - iter 380/386 - loss 0.08080162 - samples/sec: 104.70 - lr: 0.025000 |
|
2022-11-06 22:13:35,597 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:13:35,597 EPOCH 87 done: loss 0.0809 - lr 0.025000 |
|
2022-11-06 22:13:47,565 Evaluating as a multi-label problem: False |
|
2022-11-06 22:13:47,681 TEST : loss 0.0789749026298523 - f1-score (micro avg) 0.9794 |
|
2022-11-06 22:13:47,795 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 22:13:47,998 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:13:53,872 epoch 88 - iter 38/386 - loss 0.07960722 - samples/sec: 103.57 - lr: 0.025000 |
|
2022-11-06 22:13:59,254 epoch 88 - iter 76/386 - loss 0.08122546 - samples/sec: 113.04 - lr: 0.025000 |
|
2022-11-06 22:14:04,434 epoch 88 - iter 114/386 - loss 0.07933891 - samples/sec: 117.44 - lr: 0.025000 |
|
2022-11-06 22:14:09,961 epoch 88 - iter 152/386 - loss 0.07896805 - samples/sec: 110.07 - lr: 0.025000 |
|
2022-11-06 22:14:16,177 epoch 88 - iter 190/386 - loss 0.08116421 - samples/sec: 98.16 - lr: 0.025000 |
|
2022-11-06 22:14:21,535 epoch 88 - iter 228/386 - loss 0.08035744 - samples/sec: 113.55 - lr: 0.025000 |
|
2022-11-06 22:14:26,609 epoch 88 - iter 266/386 - loss 0.08058892 - samples/sec: 119.89 - lr: 0.025000 |
|
2022-11-06 22:14:32,263 epoch 88 - iter 304/386 - loss 0.08057870 - samples/sec: 107.59 - lr: 0.025000 |
|
2022-11-06 22:14:37,985 epoch 88 - iter 342/386 - loss 0.08112992 - samples/sec: 106.32 - lr: 0.025000 |
|
2022-11-06 22:14:43,722 epoch 88 - iter 380/386 - loss 0.08050531 - samples/sec: 106.03 - lr: 0.025000 |
|
2022-11-06 22:14:44,574 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:14:44,574 EPOCH 88 done: loss 0.0806 - lr 0.025000 |
|
2022-11-06 22:14:54,171 Evaluating as a multi-label problem: False |
|
2022-11-06 22:14:54,289 TEST : loss 0.07823394984006882 - f1-score (micro avg) 0.9803 |
|
2022-11-06 22:14:54,403 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 22:14:54,614 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:15:00,149 epoch 89 - iter 38/386 - loss 0.08881669 - samples/sec: 109.94 - lr: 0.025000 |
|
2022-11-06 22:15:05,572 epoch 89 - iter 76/386 - loss 0.08617115 - samples/sec: 112.18 - lr: 0.025000 |
|
2022-11-06 22:15:11,757 epoch 89 - iter 114/386 - loss 0.08675312 - samples/sec: 98.35 - lr: 0.025000 |
|
2022-11-06 22:15:17,611 epoch 89 - iter 152/386 - loss 0.08471759 - samples/sec: 103.91 - lr: 0.025000 |
|
2022-11-06 22:15:23,183 epoch 89 - iter 190/386 - loss 0.08466736 - samples/sec: 109.18 - lr: 0.025000 |
|
2022-11-06 22:15:29,113 epoch 89 - iter 228/386 - loss 0.08438120 - samples/sec: 102.59 - lr: 0.025000 |
|
2022-11-06 22:15:34,144 epoch 89 - iter 266/386 - loss 0.08433213 - samples/sec: 120.91 - lr: 0.025000 |
|
2022-11-06 22:15:39,249 epoch 89 - iter 304/386 - loss 0.08327686 - samples/sec: 119.17 - lr: 0.025000 |
|
2022-11-06 22:15:44,762 epoch 89 - iter 342/386 - loss 0.08302938 - samples/sec: 110.35 - lr: 0.025000 |
|
2022-11-06 22:15:49,944 epoch 89 - iter 380/386 - loss 0.08333523 - samples/sec: 117.41 - lr: 0.025000 |
|
2022-11-06 22:15:50,759 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:15:50,760 EPOCH 89 done: loss 0.0834 - lr 0.025000 |
|
2022-11-06 22:16:00,390 Evaluating as a multi-label problem: False |
|
2022-11-06 22:16:00,506 TEST : loss 0.07800823450088501 - f1-score (micro avg) 0.9801 |
|
2022-11-06 22:16:00,619 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 22:16:00,827 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:16:06,217 epoch 90 - iter 38/386 - loss 0.07277550 - samples/sec: 112.90 - lr: 0.025000 |
|
2022-11-06 22:16:12,219 epoch 90 - iter 76/386 - loss 0.07701800 - samples/sec: 101.35 - lr: 0.025000 |
|
2022-11-06 22:16:17,987 epoch 90 - iter 114/386 - loss 0.07742446 - samples/sec: 105.47 - lr: 0.025000 |
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2022-11-06 22:16:23,938 epoch 90 - iter 152/386 - loss 0.07881106 - samples/sec: 102.22 - lr: 0.025000 |
|
2022-11-06 22:16:29,683 epoch 90 - iter 190/386 - loss 0.07802511 - samples/sec: 105.90 - lr: 0.025000 |
|
2022-11-06 22:16:35,320 epoch 90 - iter 228/386 - loss 0.07783453 - samples/sec: 107.92 - lr: 0.025000 |
|
2022-11-06 22:16:40,941 epoch 90 - iter 266/386 - loss 0.07841678 - samples/sec: 108.23 - lr: 0.025000 |
|
2022-11-06 22:16:46,376 epoch 90 - iter 304/386 - loss 0.07848769 - samples/sec: 111.93 - lr: 0.025000 |
|
2022-11-06 22:16:51,326 epoch 90 - iter 342/386 - loss 0.07989413 - samples/sec: 122.91 - lr: 0.025000 |
|
2022-11-06 22:16:56,567 epoch 90 - iter 380/386 - loss 0.07990854 - samples/sec: 116.09 - lr: 0.025000 |
|
2022-11-06 22:16:57,414 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:16:57,414 EPOCH 90 done: loss 0.0798 - lr 0.025000 |
|
2022-11-06 22:17:07,040 Evaluating as a multi-label problem: False |
|
2022-11-06 22:17:07,155 TEST : loss 0.0782727301120758 - f1-score (micro avg) 0.9797 |
|
2022-11-06 22:17:07,269 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 22:17:07,484 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:17:13,293 epoch 91 - iter 38/386 - loss 0.07733783 - samples/sec: 104.74 - lr: 0.025000 |
|
2022-11-06 22:17:18,780 epoch 91 - iter 76/386 - loss 0.07882994 - samples/sec: 110.88 - lr: 0.025000 |
|
2022-11-06 22:17:24,473 epoch 91 - iter 114/386 - loss 0.07801837 - samples/sec: 106.85 - lr: 0.025000 |
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2022-11-06 22:17:29,980 epoch 91 - iter 152/386 - loss 0.07769611 - samples/sec: 110.48 - lr: 0.025000 |
|
2022-11-06 22:17:35,570 epoch 91 - iter 190/386 - loss 0.07877727 - samples/sec: 108.83 - lr: 0.025000 |
|
2022-11-06 22:17:41,695 epoch 91 - iter 228/386 - loss 0.08001718 - samples/sec: 99.31 - lr: 0.025000 |
|
2022-11-06 22:17:47,341 epoch 91 - iter 266/386 - loss 0.08042378 - samples/sec: 107.74 - lr: 0.025000 |
|
2022-11-06 22:17:52,607 epoch 91 - iter 304/386 - loss 0.08061679 - samples/sec: 115.53 - lr: 0.025000 |
|
2022-11-06 22:17:58,187 epoch 91 - iter 342/386 - loss 0.08023143 - samples/sec: 109.03 - lr: 0.025000 |
|
2022-11-06 22:18:02,883 epoch 91 - iter 380/386 - loss 0.08028607 - samples/sec: 129.55 - lr: 0.025000 |
|
2022-11-06 22:18:03,642 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:18:03,643 EPOCH 91 done: loss 0.0802 - lr 0.025000 |
|
2022-11-06 22:18:13,097 Evaluating as a multi-label problem: False |
|
2022-11-06 22:18:13,212 TEST : loss 0.07592158764600754 - f1-score (micro avg) 0.9801 |
|
2022-11-06 22:18:13,325 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 22:18:13,537 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:18:19,331 epoch 92 - iter 38/386 - loss 0.08023383 - samples/sec: 105.02 - lr: 0.025000 |
|
2022-11-06 22:18:24,596 epoch 92 - iter 76/386 - loss 0.07880003 - samples/sec: 115.55 - lr: 0.025000 |
|
2022-11-06 22:18:30,071 epoch 92 - iter 114/386 - loss 0.07966319 - samples/sec: 111.10 - lr: 0.025000 |
|
2022-11-06 22:18:35,373 epoch 92 - iter 152/386 - loss 0.07820587 - samples/sec: 114.74 - lr: 0.025000 |
|
2022-11-06 22:18:40,814 epoch 92 - iter 190/386 - loss 0.07957457 - samples/sec: 111.81 - lr: 0.025000 |
|
2022-11-06 22:18:46,314 epoch 92 - iter 228/386 - loss 0.08100660 - samples/sec: 110.60 - lr: 0.025000 |
|
2022-11-06 22:18:51,788 epoch 92 - iter 266/386 - loss 0.08021248 - samples/sec: 111.15 - lr: 0.025000 |
|
2022-11-06 22:18:57,733 epoch 92 - iter 304/386 - loss 0.08025273 - samples/sec: 102.32 - lr: 0.025000 |
|
2022-11-06 22:19:03,667 epoch 92 - iter 342/386 - loss 0.08017579 - samples/sec: 102.51 - lr: 0.025000 |
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2022-11-06 22:19:09,758 epoch 92 - iter 380/386 - loss 0.08044134 - samples/sec: 99.87 - lr: 0.025000 |
|
2022-11-06 22:19:10,656 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:19:10,656 EPOCH 92 done: loss 0.0804 - lr 0.025000 |
|
2022-11-06 22:19:19,504 Evaluating as a multi-label problem: False |
|
2022-11-06 22:19:19,620 TEST : loss 0.07693848758935928 - f1-score (micro avg) 0.9794 |
|
2022-11-06 22:19:19,734 BAD EPOCHS (no improvement): 2 |
|
2022-11-06 22:19:19,946 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:19:25,255 epoch 93 - iter 38/386 - loss 0.07236939 - samples/sec: 114.63 - lr: 0.025000 |
|
2022-11-06 22:19:30,943 epoch 93 - iter 76/386 - loss 0.07614718 - samples/sec: 106.95 - lr: 0.025000 |
|
2022-11-06 22:19:36,710 epoch 93 - iter 114/386 - loss 0.07729937 - samples/sec: 105.48 - lr: 0.025000 |
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2022-11-06 22:19:42,344 epoch 93 - iter 152/386 - loss 0.07799549 - samples/sec: 107.97 - lr: 0.025000 |
|
2022-11-06 22:19:48,026 epoch 93 - iter 190/386 - loss 0.07765939 - samples/sec: 107.06 - lr: 0.025000 |
|
2022-11-06 22:19:53,694 epoch 93 - iter 228/386 - loss 0.07913237 - samples/sec: 107.33 - lr: 0.025000 |
|
2022-11-06 22:19:59,951 epoch 93 - iter 266/386 - loss 0.07940271 - samples/sec: 97.22 - lr: 0.025000 |
|
2022-11-06 22:20:05,381 epoch 93 - iter 304/386 - loss 0.08045973 - samples/sec: 112.05 - lr: 0.025000 |
|
2022-11-06 22:20:10,874 epoch 93 - iter 342/386 - loss 0.08003574 - samples/sec: 110.75 - lr: 0.025000 |
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2022-11-06 22:20:16,619 epoch 93 - iter 380/386 - loss 0.07979854 - samples/sec: 105.88 - lr: 0.025000 |
|
2022-11-06 22:20:17,372 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:20:17,373 EPOCH 93 done: loss 0.0799 - lr 0.025000 |
|
2022-11-06 22:20:26,550 Evaluating as a multi-label problem: False |
|
2022-11-06 22:20:26,665 TEST : loss 0.07909691333770752 - f1-score (micro avg) 0.9797 |
|
2022-11-06 22:20:26,778 BAD EPOCHS (no improvement): 3 |
|
2022-11-06 22:20:26,979 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:20:32,580 epoch 94 - iter 38/386 - loss 0.07446764 - samples/sec: 108.63 - lr: 0.025000 |
|
2022-11-06 22:20:37,820 epoch 94 - iter 76/386 - loss 0.07660519 - samples/sec: 116.10 - lr: 0.025000 |
|
2022-11-06 22:20:43,411 epoch 94 - iter 114/386 - loss 0.07713177 - samples/sec: 108.80 - lr: 0.025000 |
|
2022-11-06 22:20:48,823 epoch 94 - iter 152/386 - loss 0.07876191 - samples/sec: 112.40 - lr: 0.025000 |
|
2022-11-06 22:20:54,987 epoch 94 - iter 190/386 - loss 0.07891465 - samples/sec: 98.70 - lr: 0.025000 |
|
2022-11-06 22:21:00,715 epoch 94 - iter 228/386 - loss 0.08002992 - samples/sec: 106.19 - lr: 0.025000 |
|
2022-11-06 22:21:06,057 epoch 94 - iter 266/386 - loss 0.08085213 - samples/sec: 113.89 - lr: 0.025000 |
|
2022-11-06 22:21:11,648 epoch 94 - iter 304/386 - loss 0.08032064 - samples/sec: 108.79 - lr: 0.025000 |
|
2022-11-06 22:21:17,202 epoch 94 - iter 342/386 - loss 0.08072521 - samples/sec: 109.52 - lr: 0.025000 |
|
2022-11-06 22:21:22,895 epoch 94 - iter 380/386 - loss 0.08026007 - samples/sec: 106.87 - lr: 0.025000 |
|
2022-11-06 22:21:23,735 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:21:23,735 EPOCH 94 done: loss 0.0799 - lr 0.025000 |
|
2022-11-06 22:21:33,272 Evaluating as a multi-label problem: False |
|
2022-11-06 22:21:33,386 TEST : loss 0.07736696302890778 - f1-score (micro avg) 0.98 |
|
2022-11-06 22:21:33,499 Epoch 94: reducing learning rate of group 0 to 1.2500e-02. |
|
2022-11-06 22:21:33,499 BAD EPOCHS (no improvement): 4 |
|
2022-11-06 22:21:33,708 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:21:39,107 epoch 95 - iter 38/386 - loss 0.08174345 - samples/sec: 112.71 - lr: 0.012500 |
|
2022-11-06 22:21:44,470 epoch 95 - iter 76/386 - loss 0.07654626 - samples/sec: 113.43 - lr: 0.012500 |
|
2022-11-06 22:21:50,355 epoch 95 - iter 114/386 - loss 0.07662746 - samples/sec: 103.36 - lr: 0.012500 |
|
2022-11-06 22:21:55,951 epoch 95 - iter 152/386 - loss 0.07713288 - samples/sec: 108.71 - lr: 0.012500 |
|
2022-11-06 22:22:01,525 epoch 95 - iter 190/386 - loss 0.07768088 - samples/sec: 109.15 - lr: 0.012500 |
|
2022-11-06 22:22:07,333 epoch 95 - iter 228/386 - loss 0.07691802 - samples/sec: 104.74 - lr: 0.012500 |
|
2022-11-06 22:22:12,698 epoch 95 - iter 266/386 - loss 0.07735595 - samples/sec: 113.38 - lr: 0.012500 |
|
2022-11-06 22:22:17,950 epoch 95 - iter 304/386 - loss 0.07722152 - samples/sec: 115.84 - lr: 0.012500 |
|
2022-11-06 22:22:23,779 epoch 95 - iter 342/386 - loss 0.07755445 - samples/sec: 104.34 - lr: 0.012500 |
|
2022-11-06 22:22:29,040 epoch 95 - iter 380/386 - loss 0.07761664 - samples/sec: 115.64 - lr: 0.012500 |
|
2022-11-06 22:22:29,870 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:22:29,870 EPOCH 95 done: loss 0.0775 - lr 0.012500 |
|
2022-11-06 22:22:39,433 Evaluating as a multi-label problem: False |
|
2022-11-06 22:22:39,548 TEST : loss 0.07741290330886841 - f1-score (micro avg) 0.9799 |
|
2022-11-06 22:22:39,660 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 22:22:39,868 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:22:45,073 epoch 96 - iter 38/386 - loss 0.07749330 - samples/sec: 116.90 - lr: 0.012500 |
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2022-11-06 22:22:50,290 epoch 96 - iter 76/386 - loss 0.07728624 - samples/sec: 116.60 - lr: 0.012500 |
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2022-11-06 22:22:55,456 epoch 96 - iter 114/386 - loss 0.07852333 - samples/sec: 117.77 - lr: 0.012500 |
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2022-11-06 22:23:00,968 epoch 96 - iter 152/386 - loss 0.07840505 - samples/sec: 110.38 - lr: 0.012500 |
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2022-11-06 22:23:06,683 epoch 96 - iter 190/386 - loss 0.07797949 - samples/sec: 107.23 - lr: 0.012500 |
|
2022-11-06 22:23:12,055 epoch 96 - iter 228/386 - loss 0.07937941 - samples/sec: 113.25 - lr: 0.012500 |
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2022-11-06 22:23:17,534 epoch 96 - iter 266/386 - loss 0.07834560 - samples/sec: 111.03 - lr: 0.012500 |
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2022-11-06 22:23:23,499 epoch 96 - iter 304/386 - loss 0.07818574 - samples/sec: 101.98 - lr: 0.012500 |
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2022-11-06 22:23:29,172 epoch 96 - iter 342/386 - loss 0.07823185 - samples/sec: 107.23 - lr: 0.012500 |
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2022-11-06 22:23:34,750 epoch 96 - iter 380/386 - loss 0.07889026 - samples/sec: 109.06 - lr: 0.012500 |
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2022-11-06 22:23:35,658 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:23:35,659 EPOCH 96 done: loss 0.0789 - lr 0.012500 |
|
2022-11-06 22:23:45,210 Evaluating as a multi-label problem: False |
|
2022-11-06 22:23:45,326 TEST : loss 0.07733169943094254 - f1-score (micro avg) 0.9796 |
|
2022-11-06 22:23:45,439 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 22:23:45,649 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:23:50,915 epoch 97 - iter 38/386 - loss 0.08544884 - samples/sec: 115.57 - lr: 0.012500 |
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2022-11-06 22:23:56,576 epoch 97 - iter 76/386 - loss 0.08138444 - samples/sec: 107.45 - lr: 0.012500 |
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2022-11-06 22:24:01,972 epoch 97 - iter 114/386 - loss 0.07902100 - samples/sec: 112.74 - lr: 0.012500 |
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2022-11-06 22:24:07,363 epoch 97 - iter 152/386 - loss 0.07840143 - samples/sec: 112.84 - lr: 0.012500 |
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2022-11-06 22:24:12,825 epoch 97 - iter 190/386 - loss 0.07712703 - samples/sec: 111.37 - lr: 0.012500 |
|
2022-11-06 22:24:18,787 epoch 97 - iter 228/386 - loss 0.07678814 - samples/sec: 102.77 - lr: 0.012500 |
|
2022-11-06 22:24:24,633 epoch 97 - iter 266/386 - loss 0.07676126 - samples/sec: 104.05 - lr: 0.012500 |
|
2022-11-06 22:24:30,835 epoch 97 - iter 304/386 - loss 0.07801854 - samples/sec: 98.08 - lr: 0.012500 |
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2022-11-06 22:24:36,203 epoch 97 - iter 342/386 - loss 0.07840287 - samples/sec: 113.33 - lr: 0.012500 |
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2022-11-06 22:24:41,478 epoch 97 - iter 380/386 - loss 0.07841984 - samples/sec: 115.32 - lr: 0.012500 |
|
2022-11-06 22:24:42,301 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:24:42,301 EPOCH 97 done: loss 0.0783 - lr 0.012500 |
|
2022-11-06 22:24:54,117 Evaluating as a multi-label problem: False |
|
2022-11-06 22:24:54,232 TEST : loss 0.07772345840930939 - f1-score (micro avg) 0.98 |
|
2022-11-06 22:24:54,344 BAD EPOCHS (no improvement): 2 |
|
2022-11-06 22:24:54,551 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:25:00,111 epoch 98 - iter 38/386 - loss 0.07439980 - samples/sec: 109.44 - lr: 0.012500 |
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2022-11-06 22:25:05,686 epoch 98 - iter 76/386 - loss 0.07645508 - samples/sec: 109.11 - lr: 0.012500 |
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2022-11-06 22:25:11,184 epoch 98 - iter 114/386 - loss 0.07708381 - samples/sec: 110.65 - lr: 0.012500 |
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2022-11-06 22:25:16,337 epoch 98 - iter 152/386 - loss 0.08009789 - samples/sec: 118.07 - lr: 0.012500 |
|
2022-11-06 22:25:21,314 epoch 98 - iter 190/386 - loss 0.07936476 - samples/sec: 122.22 - lr: 0.012500 |
|
2022-11-06 22:25:26,767 epoch 98 - iter 228/386 - loss 0.07906153 - samples/sec: 111.56 - lr: 0.012500 |
|
2022-11-06 22:25:32,821 epoch 98 - iter 266/386 - loss 0.07918697 - samples/sec: 100.50 - lr: 0.012500 |
|
2022-11-06 22:25:38,261 epoch 98 - iter 304/386 - loss 0.07882593 - samples/sec: 111.82 - lr: 0.012500 |
|
2022-11-06 22:25:43,440 epoch 98 - iter 342/386 - loss 0.07839498 - samples/sec: 117.47 - lr: 0.012500 |
|
2022-11-06 22:25:49,435 epoch 98 - iter 380/386 - loss 0.07899311 - samples/sec: 101.47 - lr: 0.012500 |
|
2022-11-06 22:25:50,290 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:25:50,290 EPOCH 98 done: loss 0.0790 - lr 0.012500 |
|
2022-11-06 22:25:59,749 Evaluating as a multi-label problem: False |
|
2022-11-06 22:25:59,865 TEST : loss 0.07763128727674484 - f1-score (micro avg) 0.9803 |
|
2022-11-06 22:25:59,979 BAD EPOCHS (no improvement): 3 |
|
2022-11-06 22:26:00,189 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:26:06,142 epoch 99 - iter 38/386 - loss 0.07254806 - samples/sec: 102.21 - lr: 0.012500 |
|
2022-11-06 22:26:11,686 epoch 99 - iter 76/386 - loss 0.07331350 - samples/sec: 109.74 - lr: 0.012500 |
|
2022-11-06 22:26:17,577 epoch 99 - iter 114/386 - loss 0.07299872 - samples/sec: 103.26 - lr: 0.012500 |
|
2022-11-06 22:26:23,460 epoch 99 - iter 152/386 - loss 0.07443824 - samples/sec: 103.39 - lr: 0.012500 |
|
2022-11-06 22:26:28,808 epoch 99 - iter 190/386 - loss 0.07449089 - samples/sec: 113.75 - lr: 0.012500 |
|
2022-11-06 22:26:33,908 epoch 99 - iter 228/386 - loss 0.07509719 - samples/sec: 119.29 - lr: 0.012500 |
|
2022-11-06 22:26:39,140 epoch 99 - iter 266/386 - loss 0.07561839 - samples/sec: 116.29 - lr: 0.012500 |
|
2022-11-06 22:26:44,840 epoch 99 - iter 304/386 - loss 0.07630032 - samples/sec: 106.71 - lr: 0.012500 |
|
2022-11-06 22:26:49,959 epoch 99 - iter 342/386 - loss 0.07606443 - samples/sec: 118.84 - lr: 0.012500 |
|
2022-11-06 22:26:55,370 epoch 99 - iter 380/386 - loss 0.07638476 - samples/sec: 113.33 - lr: 0.012500 |
|
2022-11-06 22:26:56,359 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:26:56,359 EPOCH 99 done: loss 0.0766 - lr 0.012500 |
|
2022-11-06 22:27:05,824 Evaluating as a multi-label problem: False |
|
2022-11-06 22:27:05,939 TEST : loss 0.07717061787843704 - f1-score (micro avg) 0.9801 |
|
2022-11-06 22:27:06,052 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 22:27:06,257 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:27:11,941 epoch 100 - iter 38/386 - loss 0.08360850 - samples/sec: 107.04 - lr: 0.012500 |
|
2022-11-06 22:27:17,484 epoch 100 - iter 76/386 - loss 0.07889395 - samples/sec: 109.75 - lr: 0.012500 |
|
2022-11-06 22:27:23,204 epoch 100 - iter 114/386 - loss 0.08078996 - samples/sec: 106.34 - lr: 0.012500 |
|
2022-11-06 22:27:28,890 epoch 100 - iter 152/386 - loss 0.08157095 - samples/sec: 106.99 - lr: 0.012500 |
|
2022-11-06 22:27:34,405 epoch 100 - iter 190/386 - loss 0.08048207 - samples/sec: 110.31 - lr: 0.012500 |
|
2022-11-06 22:27:39,771 epoch 100 - iter 228/386 - loss 0.07920505 - samples/sec: 113.35 - lr: 0.012500 |
|
2022-11-06 22:27:45,192 epoch 100 - iter 266/386 - loss 0.07736238 - samples/sec: 112.23 - lr: 0.012500 |
|
2022-11-06 22:27:50,358 epoch 100 - iter 304/386 - loss 0.07652413 - samples/sec: 117.75 - lr: 0.012500 |
|
2022-11-06 22:27:55,824 epoch 100 - iter 342/386 - loss 0.07592693 - samples/sec: 111.31 - lr: 0.012500 |
|
2022-11-06 22:28:01,279 epoch 100 - iter 380/386 - loss 0.07600602 - samples/sec: 111.51 - lr: 0.012500 |
|
2022-11-06 22:28:02,152 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:28:02,152 EPOCH 100 done: loss 0.0759 - lr 0.012500 |
|
2022-11-06 22:28:11,635 Evaluating as a multi-label problem: False |
|
2022-11-06 22:28:11,753 TEST : loss 0.07758809626102448 - f1-score (micro avg) 0.9803 |
|
2022-11-06 22:28:11,866 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 22:28:12,070 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:28:17,706 epoch 101 - iter 38/386 - loss 0.07388983 - samples/sec: 107.96 - lr: 0.012500 |
|
2022-11-06 22:28:23,437 epoch 101 - iter 76/386 - loss 0.07406827 - samples/sec: 106.16 - lr: 0.012500 |
|
2022-11-06 22:28:28,733 epoch 101 - iter 114/386 - loss 0.07275898 - samples/sec: 114.86 - lr: 0.012500 |
|
2022-11-06 22:28:34,583 epoch 101 - iter 152/386 - loss 0.07457340 - samples/sec: 104.00 - lr: 0.012500 |
|
2022-11-06 22:28:39,730 epoch 101 - iter 190/386 - loss 0.07526331 - samples/sec: 118.19 - lr: 0.012500 |
|
2022-11-06 22:28:45,750 epoch 101 - iter 228/386 - loss 0.07519061 - samples/sec: 101.05 - lr: 0.012500 |
|
2022-11-06 22:28:51,489 epoch 101 - iter 266/386 - loss 0.07529028 - samples/sec: 105.99 - lr: 0.012500 |
|
2022-11-06 22:28:56,953 epoch 101 - iter 304/386 - loss 0.07552666 - samples/sec: 111.34 - lr: 0.012500 |
|
2022-11-06 22:29:01,707 epoch 101 - iter 342/386 - loss 0.07603837 - samples/sec: 127.98 - lr: 0.012500 |
|
2022-11-06 22:29:06,807 epoch 101 - iter 380/386 - loss 0.07630310 - samples/sec: 119.28 - lr: 0.012500 |
|
2022-11-06 22:29:07,609 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:29:07,609 EPOCH 101 done: loss 0.0765 - lr 0.012500 |
|
2022-11-06 22:29:17,153 Evaluating as a multi-label problem: False |
|
2022-11-06 22:29:17,268 TEST : loss 0.07733462750911713 - f1-score (micro avg) 0.9801 |
|
2022-11-06 22:29:17,380 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 22:29:17,589 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:29:22,875 epoch 102 - iter 38/386 - loss 0.08028161 - samples/sec: 115.12 - lr: 0.012500 |
|
2022-11-06 22:29:28,787 epoch 102 - iter 76/386 - loss 0.07647839 - samples/sec: 102.89 - lr: 0.012500 |
|
2022-11-06 22:29:34,241 epoch 102 - iter 114/386 - loss 0.07459047 - samples/sec: 111.53 - lr: 0.012500 |
|
2022-11-06 22:29:39,930 epoch 102 - iter 152/386 - loss 0.07461720 - samples/sec: 106.95 - lr: 0.012500 |
|
2022-11-06 22:29:45,892 epoch 102 - iter 190/386 - loss 0.07589447 - samples/sec: 102.02 - lr: 0.012500 |
|
2022-11-06 22:29:51,280 epoch 102 - iter 228/386 - loss 0.07462336 - samples/sec: 112.92 - lr: 0.012500 |
|
2022-11-06 22:29:56,688 epoch 102 - iter 266/386 - loss 0.07534371 - samples/sec: 112.75 - lr: 0.012500 |
|
2022-11-06 22:30:02,427 epoch 102 - iter 304/386 - loss 0.07531681 - samples/sec: 106.00 - lr: 0.012500 |
|
2022-11-06 22:30:08,110 epoch 102 - iter 342/386 - loss 0.07515869 - samples/sec: 107.02 - lr: 0.012500 |
|
2022-11-06 22:30:13,062 epoch 102 - iter 380/386 - loss 0.07486919 - samples/sec: 122.85 - lr: 0.012500 |
|
2022-11-06 22:30:13,878 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:30:13,878 EPOCH 102 done: loss 0.0751 - lr 0.012500 |
|
2022-11-06 22:30:23,042 Evaluating as a multi-label problem: False |
|
2022-11-06 22:30:23,157 TEST : loss 0.07761669158935547 - f1-score (micro avg) 0.9801 |
|
2022-11-06 22:30:23,269 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 22:30:23,477 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:30:29,131 epoch 103 - iter 38/386 - loss 0.07445893 - samples/sec: 107.61 - lr: 0.012500 |
|
2022-11-06 22:30:34,529 epoch 103 - iter 76/386 - loss 0.07775874 - samples/sec: 112.69 - lr: 0.012500 |
|
2022-11-06 22:30:39,927 epoch 103 - iter 114/386 - loss 0.07897023 - samples/sec: 112.71 - lr: 0.012500 |
|
2022-11-06 22:30:45,537 epoch 103 - iter 152/386 - loss 0.07848129 - samples/sec: 108.44 - lr: 0.012500 |
|
2022-11-06 22:30:51,233 epoch 103 - iter 190/386 - loss 0.07676500 - samples/sec: 106.79 - lr: 0.012500 |
|
2022-11-06 22:30:56,738 epoch 103 - iter 228/386 - loss 0.07555006 - samples/sec: 110.51 - lr: 0.012500 |
|
2022-11-06 22:31:02,068 epoch 103 - iter 266/386 - loss 0.07606481 - samples/sec: 114.13 - lr: 0.012500 |
|
2022-11-06 22:31:07,290 epoch 103 - iter 304/386 - loss 0.07608797 - samples/sec: 116.48 - lr: 0.012500 |
|
2022-11-06 22:31:13,424 epoch 103 - iter 342/386 - loss 0.07538846 - samples/sec: 99.72 - lr: 0.012500 |
|
2022-11-06 22:31:19,479 epoch 103 - iter 380/386 - loss 0.07560503 - samples/sec: 100.47 - lr: 0.012500 |
|
2022-11-06 22:31:20,161 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:31:20,162 EPOCH 103 done: loss 0.0753 - lr 0.012500 |
|
2022-11-06 22:31:29,000 Evaluating as a multi-label problem: False |
|
2022-11-06 22:31:29,114 TEST : loss 0.07814455777406693 - f1-score (micro avg) 0.9797 |
|
2022-11-06 22:31:29,226 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 22:31:29,435 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:31:35,248 epoch 104 - iter 38/386 - loss 0.06466635 - samples/sec: 104.67 - lr: 0.012500 |
|
2022-11-06 22:31:40,662 epoch 104 - iter 76/386 - loss 0.06932147 - samples/sec: 112.38 - lr: 0.012500 |
|
2022-11-06 22:31:46,456 epoch 104 - iter 114/386 - loss 0.07324214 - samples/sec: 104.99 - lr: 0.012500 |
|
2022-11-06 22:31:52,249 epoch 104 - iter 152/386 - loss 0.07342158 - samples/sec: 105.01 - lr: 0.012500 |
|
2022-11-06 22:31:57,692 epoch 104 - iter 190/386 - loss 0.07451835 - samples/sec: 111.76 - lr: 0.012500 |
|
2022-11-06 22:32:03,008 epoch 104 - iter 228/386 - loss 0.07500854 - samples/sec: 114.46 - lr: 0.012500 |
|
2022-11-06 22:32:08,916 epoch 104 - iter 266/386 - loss 0.07423502 - samples/sec: 102.95 - lr: 0.012500 |
|
2022-11-06 22:32:14,693 epoch 104 - iter 304/386 - loss 0.07465836 - samples/sec: 105.30 - lr: 0.012500 |
|
2022-11-06 22:32:20,353 epoch 104 - iter 342/386 - loss 0.07547961 - samples/sec: 107.48 - lr: 0.012500 |
|
2022-11-06 22:32:26,022 epoch 104 - iter 380/386 - loss 0.07525945 - samples/sec: 107.31 - lr: 0.012500 |
|
2022-11-06 22:32:26,914 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:32:26,914 EPOCH 104 done: loss 0.0754 - lr 0.012500 |
|
2022-11-06 22:32:36,375 Evaluating as a multi-label problem: False |
|
2022-11-06 22:32:36,490 TEST : loss 0.07854548841714859 - f1-score (micro avg) 0.9799 |
|
2022-11-06 22:32:36,604 BAD EPOCHS (no improvement): 2 |
|
2022-11-06 22:32:36,873 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:32:42,092 epoch 105 - iter 38/386 - loss 0.07411338 - samples/sec: 116.62 - lr: 0.012500 |
|
2022-11-06 22:32:47,358 epoch 105 - iter 76/386 - loss 0.07593740 - samples/sec: 115.52 - lr: 0.012500 |
|
2022-11-06 22:32:52,835 epoch 105 - iter 114/386 - loss 0.07967368 - samples/sec: 111.94 - lr: 0.012500 |
|
2022-11-06 22:32:58,386 epoch 105 - iter 152/386 - loss 0.07724821 - samples/sec: 109.58 - lr: 0.012500 |
|
2022-11-06 22:33:04,547 epoch 105 - iter 190/386 - loss 0.07662746 - samples/sec: 98.74 - lr: 0.012500 |
|
2022-11-06 22:33:10,019 epoch 105 - iter 228/386 - loss 0.07663282 - samples/sec: 111.18 - lr: 0.012500 |
|
2022-11-06 22:33:15,439 epoch 105 - iter 266/386 - loss 0.07641141 - samples/sec: 112.23 - lr: 0.012500 |
|
2022-11-06 22:33:21,105 epoch 105 - iter 304/386 - loss 0.07529226 - samples/sec: 107.37 - lr: 0.012500 |
|
2022-11-06 22:33:27,073 epoch 105 - iter 342/386 - loss 0.07538330 - samples/sec: 101.92 - lr: 0.012500 |
|
2022-11-06 22:33:32,649 epoch 105 - iter 380/386 - loss 0.07513659 - samples/sec: 109.10 - lr: 0.012500 |
|
2022-11-06 22:33:33,521 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:33:33,521 EPOCH 105 done: loss 0.0751 - lr 0.012500 |
|
2022-11-06 22:33:43,099 Evaluating as a multi-label problem: False |
|
2022-11-06 22:33:43,215 TEST : loss 0.07858723402023315 - f1-score (micro avg) 0.9794 |
|
2022-11-06 22:33:43,330 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 22:33:43,625 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:33:49,689 epoch 106 - iter 38/386 - loss 0.06727736 - samples/sec: 100.35 - lr: 0.012500 |
|
2022-11-06 22:33:54,733 epoch 106 - iter 76/386 - loss 0.06934926 - samples/sec: 120.61 - lr: 0.012500 |
|
2022-11-06 22:34:00,089 epoch 106 - iter 114/386 - loss 0.07156163 - samples/sec: 113.60 - lr: 0.012500 |
|
2022-11-06 22:34:05,485 epoch 106 - iter 152/386 - loss 0.07347557 - samples/sec: 112.73 - lr: 0.012500 |
|
2022-11-06 22:34:10,897 epoch 106 - iter 190/386 - loss 0.07486589 - samples/sec: 112.42 - lr: 0.012500 |
|
2022-11-06 22:34:16,610 epoch 106 - iter 228/386 - loss 0.07406187 - samples/sec: 106.49 - lr: 0.012500 |
|
2022-11-06 22:34:22,290 epoch 106 - iter 266/386 - loss 0.07504310 - samples/sec: 107.09 - lr: 0.012500 |
|
2022-11-06 22:34:27,902 epoch 106 - iter 304/386 - loss 0.07553583 - samples/sec: 108.40 - lr: 0.012500 |
|
2022-11-06 22:34:33,820 epoch 106 - iter 342/386 - loss 0.07586313 - samples/sec: 102.79 - lr: 0.012500 |
|
2022-11-06 22:34:39,531 epoch 106 - iter 380/386 - loss 0.07565249 - samples/sec: 106.52 - lr: 0.012500 |
|
2022-11-06 22:34:40,287 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:34:40,287 EPOCH 106 done: loss 0.0757 - lr 0.012500 |
|
2022-11-06 22:34:49,940 Evaluating as a multi-label problem: False |
|
2022-11-06 22:34:50,056 TEST : loss 0.0764971524477005 - f1-score (micro avg) 0.9797 |
|
2022-11-06 22:34:50,168 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 22:34:50,465 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:34:55,872 epoch 107 - iter 38/386 - loss 0.07793043 - samples/sec: 112.54 - lr: 0.012500 |
|
2022-11-06 22:35:01,477 epoch 107 - iter 76/386 - loss 0.07886203 - samples/sec: 108.53 - lr: 0.012500 |
|
2022-11-06 22:35:06,360 epoch 107 - iter 114/386 - loss 0.07789126 - samples/sec: 124.61 - lr: 0.012500 |
|
2022-11-06 22:35:11,369 epoch 107 - iter 152/386 - loss 0.07771686 - samples/sec: 121.44 - lr: 0.012500 |
|
2022-11-06 22:35:17,286 epoch 107 - iter 190/386 - loss 0.07679357 - samples/sec: 102.82 - lr: 0.012500 |
|
2022-11-06 22:35:22,885 epoch 107 - iter 228/386 - loss 0.07780927 - samples/sec: 108.65 - lr: 0.012500 |
|
2022-11-06 22:35:28,831 epoch 107 - iter 266/386 - loss 0.07691362 - samples/sec: 102.30 - lr: 0.012500 |
|
2022-11-06 22:35:34,328 epoch 107 - iter 304/386 - loss 0.07767365 - samples/sec: 110.68 - lr: 0.012500 |
|
2022-11-06 22:35:39,973 epoch 107 - iter 342/386 - loss 0.07674244 - samples/sec: 107.75 - lr: 0.012500 |
|
2022-11-06 22:35:45,758 epoch 107 - iter 380/386 - loss 0.07682198 - samples/sec: 105.16 - lr: 0.012500 |
|
2022-11-06 22:35:46,691 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:35:46,691 EPOCH 107 done: loss 0.0768 - lr 0.012500 |
|
2022-11-06 22:35:58,826 Evaluating as a multi-label problem: False |
|
2022-11-06 22:35:58,940 TEST : loss 0.07759314030408859 - f1-score (micro avg) 0.9797 |
|
2022-11-06 22:35:59,054 BAD EPOCHS (no improvement): 2 |
|
2022-11-06 22:35:59,288 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:36:04,886 epoch 108 - iter 38/386 - loss 0.07772745 - samples/sec: 108.70 - lr: 0.012500 |
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2022-11-06 22:36:10,217 epoch 108 - iter 76/386 - loss 0.07956371 - samples/sec: 114.12 - lr: 0.012500 |
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2022-11-06 22:36:15,669 epoch 108 - iter 114/386 - loss 0.07712381 - samples/sec: 111.56 - lr: 0.012500 |
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2022-11-06 22:36:20,706 epoch 108 - iter 152/386 - loss 0.07614295 - samples/sec: 120.78 - lr: 0.012500 |
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2022-11-06 22:36:26,206 epoch 108 - iter 190/386 - loss 0.07566320 - samples/sec: 110.62 - lr: 0.012500 |
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2022-11-06 22:36:31,915 epoch 108 - iter 228/386 - loss 0.07528023 - samples/sec: 106.54 - lr: 0.012500 |
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2022-11-06 22:36:37,490 epoch 108 - iter 266/386 - loss 0.07548655 - samples/sec: 109.12 - lr: 0.012500 |
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2022-11-06 22:36:43,171 epoch 108 - iter 304/386 - loss 0.07645383 - samples/sec: 107.09 - lr: 0.012500 |
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2022-11-06 22:36:48,792 epoch 108 - iter 342/386 - loss 0.07723662 - samples/sec: 108.22 - lr: 0.012500 |
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2022-11-06 22:36:54,537 epoch 108 - iter 380/386 - loss 0.07675000 - samples/sec: 105.89 - lr: 0.012500 |
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2022-11-06 22:36:55,359 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:36:55,359 EPOCH 108 done: loss 0.0769 - lr 0.012500 |
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2022-11-06 22:37:05,010 Evaluating as a multi-label problem: False |
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2022-11-06 22:37:05,125 TEST : loss 0.07701174914836884 - f1-score (micro avg) 0.9797 |
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2022-11-06 22:37:05,238 BAD EPOCHS (no improvement): 3 |
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2022-11-06 22:37:05,447 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:37:11,421 epoch 109 - iter 38/386 - loss 0.07682666 - samples/sec: 101.86 - lr: 0.012500 |
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2022-11-06 22:37:16,860 epoch 109 - iter 76/386 - loss 0.07576946 - samples/sec: 111.86 - lr: 0.012500 |
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2022-11-06 22:37:23,112 epoch 109 - iter 114/386 - loss 0.07493292 - samples/sec: 97.29 - lr: 0.012500 |
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2022-11-06 22:37:28,787 epoch 109 - iter 152/386 - loss 0.07609361 - samples/sec: 107.20 - lr: 0.012500 |
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2022-11-06 22:37:33,989 epoch 109 - iter 190/386 - loss 0.07586317 - samples/sec: 116.94 - lr: 0.012500 |
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2022-11-06 22:37:39,671 epoch 109 - iter 228/386 - loss 0.07565590 - samples/sec: 107.06 - lr: 0.012500 |
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2022-11-06 22:37:44,772 epoch 109 - iter 266/386 - loss 0.07547549 - samples/sec: 119.27 - lr: 0.012500 |
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2022-11-06 22:37:49,966 epoch 109 - iter 304/386 - loss 0.07521647 - samples/sec: 117.13 - lr: 0.012500 |
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2022-11-06 22:37:55,223 epoch 109 - iter 342/386 - loss 0.07531028 - samples/sec: 115.74 - lr: 0.012500 |
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2022-11-06 22:38:00,867 epoch 109 - iter 380/386 - loss 0.07562079 - samples/sec: 107.78 - lr: 0.012500 |
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2022-11-06 22:38:01,854 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:38:01,854 EPOCH 109 done: loss 0.0754 - lr 0.012500 |
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2022-11-06 22:38:11,582 Evaluating as a multi-label problem: False |
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2022-11-06 22:38:11,697 TEST : loss 0.07831114530563354 - f1-score (micro avg) 0.9796 |
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2022-11-06 22:38:11,810 Epoch 109: reducing learning rate of group 0 to 6.2500e-03. |
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2022-11-06 22:38:11,811 BAD EPOCHS (no improvement): 4 |
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2022-11-06 22:38:12,018 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:38:17,685 epoch 110 - iter 38/386 - loss 0.08174241 - samples/sec: 107.37 - lr: 0.006250 |
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2022-11-06 22:38:23,300 epoch 110 - iter 76/386 - loss 0.07864406 - samples/sec: 108.34 - lr: 0.006250 |
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2022-11-06 22:38:28,712 epoch 110 - iter 114/386 - loss 0.07705464 - samples/sec: 112.40 - lr: 0.006250 |
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2022-11-06 22:38:34,063 epoch 110 - iter 152/386 - loss 0.07474375 - samples/sec: 113.69 - lr: 0.006250 |
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2022-11-06 22:38:39,781 epoch 110 - iter 190/386 - loss 0.07452670 - samples/sec: 106.40 - lr: 0.006250 |
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2022-11-06 22:38:45,050 epoch 110 - iter 228/386 - loss 0.07418272 - samples/sec: 115.45 - lr: 0.006250 |
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2022-11-06 22:38:49,859 epoch 110 - iter 266/386 - loss 0.07402425 - samples/sec: 126.51 - lr: 0.006250 |
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2022-11-06 22:38:55,578 epoch 110 - iter 304/386 - loss 0.07402912 - samples/sec: 106.36 - lr: 0.006250 |
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2022-11-06 22:39:01,063 epoch 110 - iter 342/386 - loss 0.07401083 - samples/sec: 110.92 - lr: 0.006250 |
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2022-11-06 22:39:06,947 epoch 110 - iter 380/386 - loss 0.07465410 - samples/sec: 103.39 - lr: 0.006250 |
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2022-11-06 22:39:07,954 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:39:07,954 EPOCH 110 done: loss 0.0747 - lr 0.006250 |
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2022-11-06 22:39:17,722 Evaluating as a multi-label problem: False |
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2022-11-06 22:39:17,837 TEST : loss 0.07766838371753693 - f1-score (micro avg) 0.9796 |
|
2022-11-06 22:39:17,950 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 22:39:18,158 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:39:23,273 epoch 111 - iter 38/386 - loss 0.07438457 - samples/sec: 118.96 - lr: 0.006250 |
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2022-11-06 22:39:28,793 epoch 111 - iter 76/386 - loss 0.07338315 - samples/sec: 110.20 - lr: 0.006250 |
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2022-11-06 22:39:34,098 epoch 111 - iter 114/386 - loss 0.07331771 - samples/sec: 114.68 - lr: 0.006250 |
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2022-11-06 22:39:39,860 epoch 111 - iter 152/386 - loss 0.07467265 - samples/sec: 105.58 - lr: 0.006250 |
|
2022-11-06 22:39:45,521 epoch 111 - iter 190/386 - loss 0.07408059 - samples/sec: 107.46 - lr: 0.006250 |
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2022-11-06 22:39:51,422 epoch 111 - iter 228/386 - loss 0.07348917 - samples/sec: 103.08 - lr: 0.006250 |
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2022-11-06 22:39:57,321 epoch 111 - iter 266/386 - loss 0.07367028 - samples/sec: 103.12 - lr: 0.006250 |
|
2022-11-06 22:40:02,596 epoch 111 - iter 304/386 - loss 0.07349484 - samples/sec: 115.33 - lr: 0.006250 |
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2022-11-06 22:40:08,382 epoch 111 - iter 342/386 - loss 0.07372678 - samples/sec: 105.14 - lr: 0.006250 |
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2022-11-06 22:40:13,289 epoch 111 - iter 380/386 - loss 0.07366151 - samples/sec: 123.97 - lr: 0.006250 |
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2022-11-06 22:40:14,051 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:40:14,051 EPOCH 111 done: loss 0.0736 - lr 0.006250 |
|
2022-11-06 22:40:23,690 Evaluating as a multi-label problem: False |
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2022-11-06 22:40:23,804 TEST : loss 0.07827350497245789 - f1-score (micro avg) 0.9799 |
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2022-11-06 22:40:23,916 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 22:40:24,123 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:40:29,099 epoch 112 - iter 38/386 - loss 0.07457649 - samples/sec: 122.30 - lr: 0.006250 |
|
2022-11-06 22:40:34,672 epoch 112 - iter 76/386 - loss 0.07390976 - samples/sec: 109.16 - lr: 0.006250 |
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2022-11-06 22:40:40,401 epoch 112 - iter 114/386 - loss 0.07481698 - samples/sec: 106.17 - lr: 0.006250 |
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2022-11-06 22:40:46,367 epoch 112 - iter 152/386 - loss 0.07362836 - samples/sec: 101.98 - lr: 0.006250 |
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2022-11-06 22:40:52,448 epoch 112 - iter 190/386 - loss 0.07372337 - samples/sec: 100.02 - lr: 0.006250 |
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2022-11-06 22:40:57,973 epoch 112 - iter 228/386 - loss 0.07390448 - samples/sec: 110.11 - lr: 0.006250 |
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2022-11-06 22:41:03,671 epoch 112 - iter 266/386 - loss 0.07383284 - samples/sec: 106.77 - lr: 0.006250 |
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2022-11-06 22:41:09,516 epoch 112 - iter 304/386 - loss 0.07359920 - samples/sec: 104.07 - lr: 0.006250 |
|
2022-11-06 22:41:14,542 epoch 112 - iter 342/386 - loss 0.07330693 - samples/sec: 121.05 - lr: 0.006250 |
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2022-11-06 22:41:19,768 epoch 112 - iter 380/386 - loss 0.07359435 - samples/sec: 116.41 - lr: 0.006250 |
|
2022-11-06 22:41:20,506 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:41:20,506 EPOCH 112 done: loss 0.0736 - lr 0.006250 |
|
2022-11-06 22:41:30,178 Evaluating as a multi-label problem: False |
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2022-11-06 22:41:30,292 TEST : loss 0.0784047469496727 - f1-score (micro avg) 0.9796 |
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2022-11-06 22:41:30,405 BAD EPOCHS (no improvement): 0 |
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2022-11-06 22:41:30,603 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:41:36,132 epoch 113 - iter 38/386 - loss 0.06745935 - samples/sec: 110.06 - lr: 0.006250 |
|
2022-11-06 22:41:41,642 epoch 113 - iter 76/386 - loss 0.07312497 - samples/sec: 110.41 - lr: 0.006250 |
|
2022-11-06 22:41:47,251 epoch 113 - iter 114/386 - loss 0.07487375 - samples/sec: 108.46 - lr: 0.006250 |
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2022-11-06 22:41:53,374 epoch 113 - iter 152/386 - loss 0.07448522 - samples/sec: 99.34 - lr: 0.006250 |
|
2022-11-06 22:41:58,986 epoch 113 - iter 190/386 - loss 0.07481588 - samples/sec: 108.39 - lr: 0.006250 |
|
2022-11-06 22:42:04,661 epoch 113 - iter 228/386 - loss 0.07481104 - samples/sec: 107.19 - lr: 0.006250 |
|
2022-11-06 22:42:09,868 epoch 113 - iter 266/386 - loss 0.07450630 - samples/sec: 116.85 - lr: 0.006250 |
|
2022-11-06 22:42:15,444 epoch 113 - iter 304/386 - loss 0.07432014 - samples/sec: 109.09 - lr: 0.006250 |
|
2022-11-06 22:42:20,828 epoch 113 - iter 342/386 - loss 0.07418859 - samples/sec: 113.00 - lr: 0.006250 |
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2022-11-06 22:42:26,222 epoch 113 - iter 380/386 - loss 0.07414788 - samples/sec: 112.77 - lr: 0.006250 |
|
2022-11-06 22:42:27,047 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:42:27,047 EPOCH 113 done: loss 0.0740 - lr 0.006250 |
|
2022-11-06 22:42:36,351 Evaluating as a multi-label problem: False |
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2022-11-06 22:42:36,466 TEST : loss 0.0782204121351242 - f1-score (micro avg) 0.9798 |
|
2022-11-06 22:42:36,579 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 22:42:36,779 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:42:42,018 epoch 114 - iter 38/386 - loss 0.06587890 - samples/sec: 116.14 - lr: 0.006250 |
|
2022-11-06 22:42:48,243 epoch 114 - iter 76/386 - loss 0.06948695 - samples/sec: 97.72 - lr: 0.006250 |
|
2022-11-06 22:42:53,714 epoch 114 - iter 114/386 - loss 0.06935897 - samples/sec: 111.20 - lr: 0.006250 |
|
2022-11-06 22:42:59,267 epoch 114 - iter 152/386 - loss 0.06830812 - samples/sec: 109.55 - lr: 0.006250 |
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2022-11-06 22:43:05,012 epoch 114 - iter 190/386 - loss 0.06990073 - samples/sec: 105.90 - lr: 0.006250 |
|
2022-11-06 22:43:10,273 epoch 114 - iter 228/386 - loss 0.07031777 - samples/sec: 115.63 - lr: 0.006250 |
|
2022-11-06 22:43:15,874 epoch 114 - iter 266/386 - loss 0.07140795 - samples/sec: 108.60 - lr: 0.006250 |
|
2022-11-06 22:43:21,628 epoch 114 - iter 304/386 - loss 0.07147415 - samples/sec: 105.72 - lr: 0.006250 |
|
2022-11-06 22:43:27,261 epoch 114 - iter 342/386 - loss 0.07159018 - samples/sec: 107.99 - lr: 0.006250 |
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2022-11-06 22:43:32,736 epoch 114 - iter 380/386 - loss 0.07193801 - samples/sec: 111.14 - lr: 0.006250 |
|
2022-11-06 22:43:33,684 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:43:33,684 EPOCH 114 done: loss 0.0717 - lr 0.006250 |
|
2022-11-06 22:43:42,618 Evaluating as a multi-label problem: False |
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2022-11-06 22:43:42,733 TEST : loss 0.07809162139892578 - f1-score (micro avg) 0.9798 |
|
2022-11-06 22:43:42,846 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 22:43:43,053 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:43:48,689 epoch 115 - iter 38/386 - loss 0.08079929 - samples/sec: 107.96 - lr: 0.006250 |
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2022-11-06 22:43:54,157 epoch 115 - iter 76/386 - loss 0.07503846 - samples/sec: 111.25 - lr: 0.006250 |
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2022-11-06 22:43:59,851 epoch 115 - iter 114/386 - loss 0.07552664 - samples/sec: 106.83 - lr: 0.006250 |
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2022-11-06 22:44:05,412 epoch 115 - iter 152/386 - loss 0.07313925 - samples/sec: 109.41 - lr: 0.006250 |
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2022-11-06 22:44:10,998 epoch 115 - iter 190/386 - loss 0.07399548 - samples/sec: 108.90 - lr: 0.006250 |
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2022-11-06 22:44:17,159 epoch 115 - iter 228/386 - loss 0.07418077 - samples/sec: 98.73 - lr: 0.006250 |
|
2022-11-06 22:44:22,490 epoch 115 - iter 266/386 - loss 0.07427701 - samples/sec: 114.12 - lr: 0.006250 |
|
2022-11-06 22:44:27,871 epoch 115 - iter 304/386 - loss 0.07325423 - samples/sec: 113.05 - lr: 0.006250 |
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2022-11-06 22:44:33,096 epoch 115 - iter 342/386 - loss 0.07281653 - samples/sec: 116.43 - lr: 0.006250 |
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2022-11-06 22:44:38,839 epoch 115 - iter 380/386 - loss 0.07338386 - samples/sec: 105.93 - lr: 0.006250 |
|
2022-11-06 22:44:39,763 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:44:39,763 EPOCH 115 done: loss 0.0737 - lr 0.006250 |
|
2022-11-06 22:44:49,211 Evaluating as a multi-label problem: False |
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2022-11-06 22:44:49,326 TEST : loss 0.07869032025337219 - f1-score (micro avg) 0.9797 |
|
2022-11-06 22:44:49,438 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 22:44:49,645 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:44:54,808 epoch 116 - iter 38/386 - loss 0.06467089 - samples/sec: 117.87 - lr: 0.006250 |
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2022-11-06 22:45:00,285 epoch 116 - iter 76/386 - loss 0.06757483 - samples/sec: 111.06 - lr: 0.006250 |
|
2022-11-06 22:45:05,972 epoch 116 - iter 114/386 - loss 0.07024725 - samples/sec: 106.98 - lr: 0.006250 |
|
2022-11-06 22:45:11,528 epoch 116 - iter 152/386 - loss 0.07050239 - samples/sec: 109.48 - lr: 0.006250 |
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2022-11-06 22:45:16,928 epoch 116 - iter 190/386 - loss 0.07115237 - samples/sec: 112.66 - lr: 0.006250 |
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2022-11-06 22:45:23,168 epoch 116 - iter 228/386 - loss 0.07166118 - samples/sec: 97.49 - lr: 0.006250 |
|
2022-11-06 22:45:28,503 epoch 116 - iter 266/386 - loss 0.07279125 - samples/sec: 114.04 - lr: 0.006250 |
|
2022-11-06 22:45:33,863 epoch 116 - iter 304/386 - loss 0.07294731 - samples/sec: 113.50 - lr: 0.006250 |
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2022-11-06 22:45:39,513 epoch 116 - iter 342/386 - loss 0.07319292 - samples/sec: 107.66 - lr: 0.006250 |
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2022-11-06 22:45:45,244 epoch 116 - iter 380/386 - loss 0.07311641 - samples/sec: 106.16 - lr: 0.006250 |
|
2022-11-06 22:45:46,149 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:45:46,149 EPOCH 116 done: loss 0.0731 - lr 0.006250 |
|
2022-11-06 22:45:55,775 Evaluating as a multi-label problem: False |
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2022-11-06 22:45:55,890 TEST : loss 0.07787258923053741 - f1-score (micro avg) 0.9799 |
|
2022-11-06 22:45:56,003 BAD EPOCHS (no improvement): 2 |
|
2022-11-06 22:45:56,208 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:46:01,914 epoch 117 - iter 38/386 - loss 0.07456506 - samples/sec: 106.63 - lr: 0.006250 |
|
2022-11-06 22:46:07,149 epoch 117 - iter 76/386 - loss 0.07301545 - samples/sec: 116.21 - lr: 0.006250 |
|
2022-11-06 22:46:12,710 epoch 117 - iter 114/386 - loss 0.07214790 - samples/sec: 109.40 - lr: 0.006250 |
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2022-11-06 22:46:18,389 epoch 117 - iter 152/386 - loss 0.07349199 - samples/sec: 107.12 - lr: 0.006250 |
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2022-11-06 22:46:24,211 epoch 117 - iter 190/386 - loss 0.07438933 - samples/sec: 104.48 - lr: 0.006250 |
|
2022-11-06 22:46:29,483 epoch 117 - iter 228/386 - loss 0.07472042 - samples/sec: 115.41 - lr: 0.006250 |
|
2022-11-06 22:46:35,736 epoch 117 - iter 266/386 - loss 0.07482219 - samples/sec: 97.28 - lr: 0.006250 |
|
2022-11-06 22:46:41,063 epoch 117 - iter 304/386 - loss 0.07409200 - samples/sec: 114.21 - lr: 0.006250 |
|
2022-11-06 22:46:46,457 epoch 117 - iter 342/386 - loss 0.07417828 - samples/sec: 112.77 - lr: 0.006250 |
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2022-11-06 22:46:51,990 epoch 117 - iter 380/386 - loss 0.07410059 - samples/sec: 109.95 - lr: 0.006250 |
|
2022-11-06 22:46:52,769 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:46:52,769 EPOCH 117 done: loss 0.0740 - lr 0.006250 |
|
2022-11-06 22:47:02,415 Evaluating as a multi-label problem: False |
|
2022-11-06 22:47:02,530 TEST : loss 0.07921639084815979 - f1-score (micro avg) 0.9794 |
|
2022-11-06 22:47:02,643 BAD EPOCHS (no improvement): 3 |
|
2022-11-06 22:47:02,849 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:47:08,496 epoch 118 - iter 38/386 - loss 0.07675392 - samples/sec: 107.75 - lr: 0.006250 |
|
2022-11-06 22:47:14,016 epoch 118 - iter 76/386 - loss 0.07527668 - samples/sec: 110.22 - lr: 0.006250 |
|
2022-11-06 22:47:18,927 epoch 118 - iter 114/386 - loss 0.07337067 - samples/sec: 123.87 - lr: 0.006250 |
|
2022-11-06 22:47:24,183 epoch 118 - iter 152/386 - loss 0.07340006 - samples/sec: 115.75 - lr: 0.006250 |
|
2022-11-06 22:47:29,668 epoch 118 - iter 190/386 - loss 0.07289468 - samples/sec: 110.90 - lr: 0.006250 |
|
2022-11-06 22:47:35,382 epoch 118 - iter 228/386 - loss 0.07318162 - samples/sec: 106.47 - lr: 0.006250 |
|
2022-11-06 22:47:40,963 epoch 118 - iter 266/386 - loss 0.07385145 - samples/sec: 109.01 - lr: 0.006250 |
|
2022-11-06 22:47:46,511 epoch 118 - iter 304/386 - loss 0.07402890 - samples/sec: 109.63 - lr: 0.006250 |
|
2022-11-06 22:47:52,857 epoch 118 - iter 342/386 - loss 0.07374341 - samples/sec: 95.87 - lr: 0.006250 |
|
2022-11-06 22:47:58,354 epoch 118 - iter 380/386 - loss 0.07366664 - samples/sec: 110.66 - lr: 0.006250 |
|
2022-11-06 22:47:59,163 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:47:59,163 EPOCH 118 done: loss 0.0738 - lr 0.006250 |
|
2022-11-06 22:48:11,151 Evaluating as a multi-label problem: False |
|
2022-11-06 22:48:11,266 TEST : loss 0.07913336902856827 - f1-score (micro avg) 0.9798 |
|
2022-11-06 22:48:11,380 Epoch 118: reducing learning rate of group 0 to 3.1250e-03. |
|
2022-11-06 22:48:11,380 BAD EPOCHS (no improvement): 4 |
|
2022-11-06 22:48:11,579 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:48:17,130 epoch 119 - iter 38/386 - loss 0.08441339 - samples/sec: 109.62 - lr: 0.003125 |
|
2022-11-06 22:48:23,068 epoch 119 - iter 76/386 - loss 0.07742126 - samples/sec: 102.45 - lr: 0.003125 |
|
2022-11-06 22:48:28,362 epoch 119 - iter 114/386 - loss 0.07506273 - samples/sec: 114.92 - lr: 0.003125 |
|
2022-11-06 22:48:33,790 epoch 119 - iter 152/386 - loss 0.07328483 - samples/sec: 112.06 - lr: 0.003125 |
|
2022-11-06 22:48:39,044 epoch 119 - iter 190/386 - loss 0.07163464 - samples/sec: 115.78 - lr: 0.003125 |
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2022-11-06 22:48:44,770 epoch 119 - iter 228/386 - loss 0.07048723 - samples/sec: 106.24 - lr: 0.003125 |
|
2022-11-06 22:48:50,324 epoch 119 - iter 266/386 - loss 0.07111069 - samples/sec: 109.54 - lr: 0.003125 |
|
2022-11-06 22:48:55,700 epoch 119 - iter 304/386 - loss 0.07159411 - samples/sec: 113.16 - lr: 0.003125 |
|
2022-11-06 22:49:01,783 epoch 119 - iter 342/386 - loss 0.07142949 - samples/sec: 100.01 - lr: 0.003125 |
|
2022-11-06 22:49:06,925 epoch 119 - iter 380/386 - loss 0.07080463 - samples/sec: 118.30 - lr: 0.003125 |
|
2022-11-06 22:49:07,684 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:49:07,684 EPOCH 119 done: loss 0.0707 - lr 0.003125 |
|
2022-11-06 22:49:17,305 Evaluating as a multi-label problem: False |
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2022-11-06 22:49:17,420 TEST : loss 0.07869245857000351 - f1-score (micro avg) 0.9798 |
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2022-11-06 22:49:17,533 BAD EPOCHS (no improvement): 0 |
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2022-11-06 22:49:17,804 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:49:23,240 epoch 120 - iter 38/386 - loss 0.07003334 - samples/sec: 111.93 - lr: 0.003125 |
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2022-11-06 22:49:28,407 epoch 120 - iter 76/386 - loss 0.07241340 - samples/sec: 117.74 - lr: 0.003125 |
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2022-11-06 22:49:34,114 epoch 120 - iter 114/386 - loss 0.07110733 - samples/sec: 106.59 - lr: 0.003125 |
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2022-11-06 22:49:39,401 epoch 120 - iter 152/386 - loss 0.07101024 - samples/sec: 115.06 - lr: 0.003125 |
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2022-11-06 22:49:44,739 epoch 120 - iter 190/386 - loss 0.07154690 - samples/sec: 113.95 - lr: 0.003125 |
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2022-11-06 22:49:51,008 epoch 120 - iter 228/386 - loss 0.07106011 - samples/sec: 97.04 - lr: 0.003125 |
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2022-11-06 22:49:56,441 epoch 120 - iter 266/386 - loss 0.07079481 - samples/sec: 111.97 - lr: 0.003125 |
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2022-11-06 22:50:01,937 epoch 120 - iter 304/386 - loss 0.07116823 - samples/sec: 110.70 - lr: 0.003125 |
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2022-11-06 22:50:07,609 epoch 120 - iter 342/386 - loss 0.07116696 - samples/sec: 107.25 - lr: 0.003125 |
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2022-11-06 22:50:13,211 epoch 120 - iter 380/386 - loss 0.07097452 - samples/sec: 108.59 - lr: 0.003125 |
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2022-11-06 22:50:14,248 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:50:14,248 EPOCH 120 done: loss 0.0710 - lr 0.003125 |
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2022-11-06 22:50:23,902 Evaluating as a multi-label problem: False |
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2022-11-06 22:50:24,018 TEST : loss 0.07862657308578491 - f1-score (micro avg) 0.9795 |
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2022-11-06 22:50:24,131 BAD EPOCHS (no improvement): 1 |
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2022-11-06 22:50:24,426 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:50:30,014 epoch 121 - iter 38/386 - loss 0.07008204 - samples/sec: 108.91 - lr: 0.003125 |
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2022-11-06 22:50:35,466 epoch 121 - iter 76/386 - loss 0.07665982 - samples/sec: 111.58 - lr: 0.003125 |
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2022-11-06 22:50:41,151 epoch 121 - iter 114/386 - loss 0.07515720 - samples/sec: 107.01 - lr: 0.003125 |
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2022-11-06 22:50:46,784 epoch 121 - iter 152/386 - loss 0.07385046 - samples/sec: 107.98 - lr: 0.003125 |
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2022-11-06 22:50:52,336 epoch 121 - iter 190/386 - loss 0.07283816 - samples/sec: 109.58 - lr: 0.003125 |
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2022-11-06 22:50:57,812 epoch 121 - iter 228/386 - loss 0.07269037 - samples/sec: 111.10 - lr: 0.003125 |
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2022-11-06 22:51:02,881 epoch 121 - iter 266/386 - loss 0.07269133 - samples/sec: 120.01 - lr: 0.003125 |
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2022-11-06 22:51:08,459 epoch 121 - iter 304/386 - loss 0.07326572 - samples/sec: 109.06 - lr: 0.003125 |
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2022-11-06 22:51:14,108 epoch 121 - iter 342/386 - loss 0.07365154 - samples/sec: 107.69 - lr: 0.003125 |
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2022-11-06 22:51:20,029 epoch 121 - iter 380/386 - loss 0.07361047 - samples/sec: 102.75 - lr: 0.003125 |
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2022-11-06 22:51:20,813 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:51:20,813 EPOCH 121 done: loss 0.0738 - lr 0.003125 |
|
2022-11-06 22:51:30,343 Evaluating as a multi-label problem: False |
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2022-11-06 22:51:30,457 TEST : loss 0.07829055935144424 - f1-score (micro avg) 0.9796 |
|
2022-11-06 22:51:30,571 BAD EPOCHS (no improvement): 2 |
|
2022-11-06 22:51:30,867 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:51:36,365 epoch 122 - iter 38/386 - loss 0.07587148 - samples/sec: 110.68 - lr: 0.003125 |
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2022-11-06 22:51:42,507 epoch 122 - iter 76/386 - loss 0.07060888 - samples/sec: 99.04 - lr: 0.003125 |
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2022-11-06 22:51:48,139 epoch 122 - iter 114/386 - loss 0.07060573 - samples/sec: 108.01 - lr: 0.003125 |
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2022-11-06 22:51:53,462 epoch 122 - iter 152/386 - loss 0.07077425 - samples/sec: 114.28 - lr: 0.003125 |
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2022-11-06 22:51:59,291 epoch 122 - iter 190/386 - loss 0.07107700 - samples/sec: 104.36 - lr: 0.003125 |
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2022-11-06 22:52:04,979 epoch 122 - iter 228/386 - loss 0.07241594 - samples/sec: 106.95 - lr: 0.003125 |
|
2022-11-06 22:52:10,324 epoch 122 - iter 266/386 - loss 0.07267496 - samples/sec: 113.82 - lr: 0.003125 |
|
2022-11-06 22:52:16,139 epoch 122 - iter 304/386 - loss 0.07311927 - samples/sec: 104.63 - lr: 0.003125 |
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2022-11-06 22:52:21,712 epoch 122 - iter 342/386 - loss 0.07384208 - samples/sec: 109.15 - lr: 0.003125 |
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2022-11-06 22:52:26,791 epoch 122 - iter 380/386 - loss 0.07386006 - samples/sec: 119.79 - lr: 0.003125 |
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2022-11-06 22:52:27,544 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:52:27,544 EPOCH 122 done: loss 0.0742 - lr 0.003125 |
|
2022-11-06 22:52:37,264 Evaluating as a multi-label problem: False |
|
2022-11-06 22:52:37,379 TEST : loss 0.07821225374937057 - f1-score (micro avg) 0.9796 |
|
2022-11-06 22:52:37,492 BAD EPOCHS (no improvement): 3 |
|
2022-11-06 22:52:37,769 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:52:43,801 epoch 123 - iter 38/386 - loss 0.07069385 - samples/sec: 100.86 - lr: 0.003125 |
|
2022-11-06 22:52:49,323 epoch 123 - iter 76/386 - loss 0.07225030 - samples/sec: 110.17 - lr: 0.003125 |
|
2022-11-06 22:52:55,191 epoch 123 - iter 114/386 - loss 0.07087317 - samples/sec: 103.67 - lr: 0.003125 |
|
2022-11-06 22:53:00,530 epoch 123 - iter 152/386 - loss 0.07098515 - samples/sec: 113.94 - lr: 0.003125 |
|
2022-11-06 22:53:05,949 epoch 123 - iter 190/386 - loss 0.07226604 - samples/sec: 112.26 - lr: 0.003125 |
|
2022-11-06 22:53:11,126 epoch 123 - iter 228/386 - loss 0.07236956 - samples/sec: 117.52 - lr: 0.003125 |
|
2022-11-06 22:53:17,082 epoch 123 - iter 266/386 - loss 0.07276559 - samples/sec: 102.15 - lr: 0.003125 |
|
2022-11-06 22:53:22,656 epoch 123 - iter 304/386 - loss 0.07227973 - samples/sec: 109.12 - lr: 0.003125 |
|
2022-11-06 22:53:28,107 epoch 123 - iter 342/386 - loss 0.07257929 - samples/sec: 111.61 - lr: 0.003125 |
|
2022-11-06 22:53:33,469 epoch 123 - iter 380/386 - loss 0.07230997 - samples/sec: 113.46 - lr: 0.003125 |
|
2022-11-06 22:53:34,176 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:53:34,176 EPOCH 123 done: loss 0.0724 - lr 0.003125 |
|
2022-11-06 22:53:43,848 Evaluating as a multi-label problem: False |
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2022-11-06 22:53:43,963 TEST : loss 0.07795599102973938 - f1-score (micro avg) 0.9795 |
|
2022-11-06 22:53:44,077 Epoch 123: reducing learning rate of group 0 to 1.5625e-03. |
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2022-11-06 22:53:44,077 BAD EPOCHS (no improvement): 4 |
|
2022-11-06 22:53:44,282 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:53:50,236 epoch 124 - iter 38/386 - loss 0.07453479 - samples/sec: 102.19 - lr: 0.001563 |
|
2022-11-06 22:53:55,507 epoch 124 - iter 76/386 - loss 0.07387122 - samples/sec: 115.43 - lr: 0.001563 |
|
2022-11-06 22:54:00,969 epoch 124 - iter 114/386 - loss 0.07305453 - samples/sec: 111.37 - lr: 0.001563 |
|
2022-11-06 22:54:07,025 epoch 124 - iter 152/386 - loss 0.07218372 - samples/sec: 100.45 - lr: 0.001563 |
|
2022-11-06 22:54:12,843 epoch 124 - iter 190/386 - loss 0.07196633 - samples/sec: 104.56 - lr: 0.001563 |
|
2022-11-06 22:54:18,154 epoch 124 - iter 228/386 - loss 0.07159715 - samples/sec: 114.53 - lr: 0.001563 |
|
2022-11-06 22:54:23,388 epoch 124 - iter 266/386 - loss 0.07198522 - samples/sec: 116.24 - lr: 0.001563 |
|
2022-11-06 22:54:29,116 epoch 124 - iter 304/386 - loss 0.07176734 - samples/sec: 106.21 - lr: 0.001563 |
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2022-11-06 22:54:34,933 epoch 124 - iter 342/386 - loss 0.07178848 - samples/sec: 104.56 - lr: 0.001563 |
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2022-11-06 22:54:40,217 epoch 124 - iter 380/386 - loss 0.07159231 - samples/sec: 115.14 - lr: 0.001563 |
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2022-11-06 22:54:40,898 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:54:40,898 EPOCH 124 done: loss 0.0716 - lr 0.001563 |
|
2022-11-06 22:54:50,281 Evaluating as a multi-label problem: False |
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2022-11-06 22:54:50,395 TEST : loss 0.0781024768948555 - f1-score (micro avg) 0.9795 |
|
2022-11-06 22:54:50,508 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 22:54:50,716 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:54:56,516 epoch 125 - iter 38/386 - loss 0.06603111 - samples/sec: 104.91 - lr: 0.001563 |
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2022-11-06 22:55:02,113 epoch 125 - iter 76/386 - loss 0.07181574 - samples/sec: 108.70 - lr: 0.001563 |
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2022-11-06 22:55:07,785 epoch 125 - iter 114/386 - loss 0.07095853 - samples/sec: 107.24 - lr: 0.001563 |
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2022-11-06 22:55:13,685 epoch 125 - iter 152/386 - loss 0.06870419 - samples/sec: 103.11 - lr: 0.001563 |
|
2022-11-06 22:55:19,200 epoch 125 - iter 190/386 - loss 0.06850812 - samples/sec: 110.30 - lr: 0.001563 |
|
2022-11-06 22:55:24,478 epoch 125 - iter 228/386 - loss 0.06907321 - samples/sec: 115.27 - lr: 0.001563 |
|
2022-11-06 22:55:29,890 epoch 125 - iter 266/386 - loss 0.07039809 - samples/sec: 112.39 - lr: 0.001563 |
|
2022-11-06 22:55:35,805 epoch 125 - iter 304/386 - loss 0.07069692 - samples/sec: 102.84 - lr: 0.001563 |
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2022-11-06 22:55:41,538 epoch 125 - iter 342/386 - loss 0.07081859 - samples/sec: 106.11 - lr: 0.001563 |
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2022-11-06 22:55:46,898 epoch 125 - iter 380/386 - loss 0.07078155 - samples/sec: 113.51 - lr: 0.001563 |
|
2022-11-06 22:55:47,710 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:55:47,710 EPOCH 125 done: loss 0.0713 - lr 0.001563 |
|
2022-11-06 22:55:56,543 Evaluating as a multi-label problem: False |
|
2022-11-06 22:55:56,659 TEST : loss 0.0782727301120758 - f1-score (micro avg) 0.9793 |
|
2022-11-06 22:55:56,772 BAD EPOCHS (no improvement): 2 |
|
2022-11-06 22:55:56,972 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:56:02,610 epoch 126 - iter 38/386 - loss 0.07739603 - samples/sec: 107.91 - lr: 0.001563 |
|
2022-11-06 22:56:08,430 epoch 126 - iter 76/386 - loss 0.07644368 - samples/sec: 104.53 - lr: 0.001563 |
|
2022-11-06 22:56:13,909 epoch 126 - iter 114/386 - loss 0.07472416 - samples/sec: 111.03 - lr: 0.001563 |
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2022-11-06 22:56:19,773 epoch 126 - iter 152/386 - loss 0.07530828 - samples/sec: 103.74 - lr: 0.001563 |
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2022-11-06 22:56:25,801 epoch 126 - iter 190/386 - loss 0.07487976 - samples/sec: 100.92 - lr: 0.001563 |
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2022-11-06 22:56:31,148 epoch 126 - iter 228/386 - loss 0.07432315 - samples/sec: 113.77 - lr: 0.001563 |
|
2022-11-06 22:56:36,614 epoch 126 - iter 266/386 - loss 0.07569476 - samples/sec: 111.29 - lr: 0.001563 |
|
2022-11-06 22:56:42,041 epoch 126 - iter 304/386 - loss 0.07498686 - samples/sec: 112.11 - lr: 0.001563 |
|
2022-11-06 22:56:47,304 epoch 126 - iter 342/386 - loss 0.07493999 - samples/sec: 115.59 - lr: 0.001563 |
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2022-11-06 22:56:53,067 epoch 126 - iter 380/386 - loss 0.07474151 - samples/sec: 105.56 - lr: 0.001563 |
|
2022-11-06 22:56:54,028 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:56:54,028 EPOCH 126 done: loss 0.0750 - lr 0.001563 |
|
2022-11-06 22:57:03,343 Evaluating as a multi-label problem: False |
|
2022-11-06 22:57:03,458 TEST : loss 0.07818238437175751 - f1-score (micro avg) 0.9794 |
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2022-11-06 22:57:03,571 BAD EPOCHS (no improvement): 3 |
|
2022-11-06 22:57:03,777 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:57:08,565 epoch 127 - iter 38/386 - loss 0.07566822 - samples/sec: 127.10 - lr: 0.001563 |
|
2022-11-06 22:57:13,988 epoch 127 - iter 76/386 - loss 0.07792866 - samples/sec: 112.19 - lr: 0.001563 |
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2022-11-06 22:57:19,657 epoch 127 - iter 114/386 - loss 0.07648305 - samples/sec: 107.29 - lr: 0.001563 |
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2022-11-06 22:57:25,348 epoch 127 - iter 152/386 - loss 0.07462793 - samples/sec: 106.89 - lr: 0.001563 |
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2022-11-06 22:57:31,158 epoch 127 - iter 190/386 - loss 0.07373016 - samples/sec: 104.70 - lr: 0.001563 |
|
2022-11-06 22:57:36,849 epoch 127 - iter 228/386 - loss 0.07276951 - samples/sec: 106.90 - lr: 0.001563 |
|
2022-11-06 22:57:42,857 epoch 127 - iter 266/386 - loss 0.07281459 - samples/sec: 101.26 - lr: 0.001563 |
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2022-11-06 22:57:48,385 epoch 127 - iter 304/386 - loss 0.07252182 - samples/sec: 110.05 - lr: 0.001563 |
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2022-11-06 22:57:53,642 epoch 127 - iter 342/386 - loss 0.07222995 - samples/sec: 115.71 - lr: 0.001563 |
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2022-11-06 22:57:59,416 epoch 127 - iter 380/386 - loss 0.07296185 - samples/sec: 105.37 - lr: 0.001563 |
|
2022-11-06 22:58:00,242 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:58:00,242 EPOCH 127 done: loss 0.0729 - lr 0.001563 |
|
2022-11-06 22:58:09,831 Evaluating as a multi-label problem: False |
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2022-11-06 22:58:09,945 TEST : loss 0.07828076183795929 - f1-score (micro avg) 0.9793 |
|
2022-11-06 22:58:10,058 Epoch 127: reducing learning rate of group 0 to 7.8125e-04. |
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2022-11-06 22:58:10,059 BAD EPOCHS (no improvement): 4 |
|
2022-11-06 22:58:10,266 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:58:15,464 epoch 128 - iter 38/386 - loss 0.06787719 - samples/sec: 117.08 - lr: 0.000781 |
|
2022-11-06 22:58:20,646 epoch 128 - iter 76/386 - loss 0.06892049 - samples/sec: 117.40 - lr: 0.000781 |
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2022-11-06 22:58:26,003 epoch 128 - iter 114/386 - loss 0.06771139 - samples/sec: 113.54 - lr: 0.000781 |
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2022-11-06 22:58:32,117 epoch 128 - iter 152/386 - loss 0.06817545 - samples/sec: 99.51 - lr: 0.000781 |
|
2022-11-06 22:58:37,740 epoch 128 - iter 190/386 - loss 0.06973778 - samples/sec: 108.18 - lr: 0.000781 |
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2022-11-06 22:58:43,253 epoch 128 - iter 228/386 - loss 0.06980534 - samples/sec: 110.34 - lr: 0.000781 |
|
2022-11-06 22:58:49,035 epoch 128 - iter 266/386 - loss 0.07035821 - samples/sec: 105.22 - lr: 0.000781 |
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2022-11-06 22:58:54,939 epoch 128 - iter 304/386 - loss 0.07045187 - samples/sec: 103.03 - lr: 0.000781 |
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2022-11-06 22:59:00,489 epoch 128 - iter 342/386 - loss 0.07072151 - samples/sec: 109.62 - lr: 0.000781 |
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2022-11-06 22:59:05,643 epoch 128 - iter 380/386 - loss 0.07044890 - samples/sec: 118.04 - lr: 0.000781 |
|
2022-11-06 22:59:06,646 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 22:59:06,646 EPOCH 128 done: loss 0.0703 - lr 0.000781 |
|
2022-11-06 22:59:18,654 Evaluating as a multi-label problem: False |
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2022-11-06 22:59:18,768 TEST : loss 0.07819060236215591 - f1-score (micro avg) 0.9793 |
|
2022-11-06 22:59:18,881 BAD EPOCHS (no improvement): 0 |
|
2022-11-06 22:59:19,088 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 22:59:24,916 epoch 129 - iter 38/386 - loss 0.07275281 - samples/sec: 104.40 - lr: 0.000781 |
|
2022-11-06 22:59:29,978 epoch 129 - iter 76/386 - loss 0.07363556 - samples/sec: 120.18 - lr: 0.000781 |
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2022-11-06 22:59:35,388 epoch 129 - iter 114/386 - loss 0.07430612 - samples/sec: 112.45 - lr: 0.000781 |
|
2022-11-06 22:59:40,922 epoch 129 - iter 152/386 - loss 0.07419195 - samples/sec: 109.93 - lr: 0.000781 |
|
2022-11-06 22:59:46,863 epoch 129 - iter 190/386 - loss 0.07384624 - samples/sec: 102.40 - lr: 0.000781 |
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2022-11-06 22:59:52,430 epoch 129 - iter 228/386 - loss 0.07418418 - samples/sec: 109.27 - lr: 0.000781 |
|
2022-11-06 22:59:58,146 epoch 129 - iter 266/386 - loss 0.07356684 - samples/sec: 106.43 - lr: 0.000781 |
|
2022-11-06 23:00:03,937 epoch 129 - iter 304/386 - loss 0.07393466 - samples/sec: 105.05 - lr: 0.000781 |
|
2022-11-06 23:00:09,128 epoch 129 - iter 342/386 - loss 0.07341780 - samples/sec: 117.19 - lr: 0.000781 |
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2022-11-06 23:00:14,745 epoch 129 - iter 380/386 - loss 0.07290983 - samples/sec: 108.30 - lr: 0.000781 |
|
2022-11-06 23:00:15,530 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 23:00:15,530 EPOCH 129 done: loss 0.0730 - lr 0.000781 |
|
2022-11-06 23:00:25,171 Evaluating as a multi-label problem: False |
|
2022-11-06 23:00:25,286 TEST : loss 0.07834754884243011 - f1-score (micro avg) 0.9793 |
|
2022-11-06 23:00:25,398 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 23:00:25,604 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 23:00:31,190 epoch 130 - iter 38/386 - loss 0.07424163 - samples/sec: 108.93 - lr: 0.000781 |
|
2022-11-06 23:00:37,401 epoch 130 - iter 76/386 - loss 0.07589137 - samples/sec: 97.93 - lr: 0.000781 |
|
2022-11-06 23:00:42,682 epoch 130 - iter 114/386 - loss 0.07505534 - samples/sec: 115.21 - lr: 0.000781 |
|
2022-11-06 23:00:48,121 epoch 130 - iter 152/386 - loss 0.07513815 - samples/sec: 111.85 - lr: 0.000781 |
|
2022-11-06 23:00:53,956 epoch 130 - iter 190/386 - loss 0.07341735 - samples/sec: 104.26 - lr: 0.000781 |
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2022-11-06 23:00:59,379 epoch 130 - iter 228/386 - loss 0.07319684 - samples/sec: 112.18 - lr: 0.000781 |
|
2022-11-06 23:01:04,834 epoch 130 - iter 266/386 - loss 0.07297365 - samples/sec: 111.50 - lr: 0.000781 |
|
2022-11-06 23:01:10,560 epoch 130 - iter 304/386 - loss 0.07221610 - samples/sec: 106.24 - lr: 0.000781 |
|
2022-11-06 23:01:16,153 epoch 130 - iter 342/386 - loss 0.07171895 - samples/sec: 108.77 - lr: 0.000781 |
|
2022-11-06 23:01:21,459 epoch 130 - iter 380/386 - loss 0.07161407 - samples/sec: 114.65 - lr: 0.000781 |
|
2022-11-06 23:01:22,369 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 23:01:22,369 EPOCH 130 done: loss 0.0716 - lr 0.000781 |
|
2022-11-06 23:01:31,982 Evaluating as a multi-label problem: False |
|
2022-11-06 23:01:32,097 TEST : loss 0.07843586802482605 - f1-score (micro avg) 0.9793 |
|
2022-11-06 23:01:32,209 BAD EPOCHS (no improvement): 2 |
|
2022-11-06 23:01:32,410 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 23:01:38,329 epoch 131 - iter 38/386 - loss 0.06891126 - samples/sec: 102.79 - lr: 0.000781 |
|
2022-11-06 23:01:44,462 epoch 131 - iter 76/386 - loss 0.07240625 - samples/sec: 99.19 - lr: 0.000781 |
|
2022-11-06 23:01:49,997 epoch 131 - iter 114/386 - loss 0.06907713 - samples/sec: 109.91 - lr: 0.000781 |
|
2022-11-06 23:01:55,666 epoch 131 - iter 152/386 - loss 0.06824256 - samples/sec: 107.30 - lr: 0.000781 |
|
2022-11-06 23:02:00,565 epoch 131 - iter 190/386 - loss 0.06781263 - samples/sec: 124.19 - lr: 0.000781 |
|
2022-11-06 23:02:06,017 epoch 131 - iter 228/386 - loss 0.06909911 - samples/sec: 111.59 - lr: 0.000781 |
|
2022-11-06 23:02:11,619 epoch 131 - iter 266/386 - loss 0.06976854 - samples/sec: 108.59 - lr: 0.000781 |
|
2022-11-06 23:02:17,071 epoch 131 - iter 304/386 - loss 0.07020506 - samples/sec: 111.58 - lr: 0.000781 |
|
2022-11-06 23:02:22,544 epoch 131 - iter 342/386 - loss 0.07057120 - samples/sec: 111.14 - lr: 0.000781 |
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2022-11-06 23:02:28,026 epoch 131 - iter 380/386 - loss 0.07018851 - samples/sec: 110.98 - lr: 0.000781 |
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2022-11-06 23:02:28,830 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 23:02:28,830 EPOCH 131 done: loss 0.0703 - lr 0.000781 |
|
2022-11-06 23:02:38,525 Evaluating as a multi-label problem: False |
|
2022-11-06 23:02:38,640 TEST : loss 0.07843144983053207 - f1-score (micro avg) 0.9793 |
|
2022-11-06 23:02:38,753 BAD EPOCHS (no improvement): 3 |
|
2022-11-06 23:02:38,953 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 23:02:44,737 epoch 132 - iter 38/386 - loss 0.06893361 - samples/sec: 105.20 - lr: 0.000781 |
|
2022-11-06 23:02:50,682 epoch 132 - iter 76/386 - loss 0.07274241 - samples/sec: 102.32 - lr: 0.000781 |
|
2022-11-06 23:02:56,233 epoch 132 - iter 114/386 - loss 0.07379979 - samples/sec: 109.59 - lr: 0.000781 |
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2022-11-06 23:03:01,739 epoch 132 - iter 152/386 - loss 0.07395336 - samples/sec: 110.49 - lr: 0.000781 |
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2022-11-06 23:03:07,196 epoch 132 - iter 190/386 - loss 0.07211236 - samples/sec: 111.49 - lr: 0.000781 |
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2022-11-06 23:03:12,542 epoch 132 - iter 228/386 - loss 0.07159589 - samples/sec: 113.79 - lr: 0.000781 |
|
2022-11-06 23:03:18,250 epoch 132 - iter 266/386 - loss 0.07132845 - samples/sec: 106.58 - lr: 0.000781 |
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2022-11-06 23:03:23,643 epoch 132 - iter 304/386 - loss 0.07088838 - samples/sec: 112.80 - lr: 0.000781 |
|
2022-11-06 23:03:29,147 epoch 132 - iter 342/386 - loss 0.07061821 - samples/sec: 110.53 - lr: 0.000781 |
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2022-11-06 23:03:34,744 epoch 132 - iter 380/386 - loss 0.07135944 - samples/sec: 108.68 - lr: 0.000781 |
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2022-11-06 23:03:35,383 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 23:03:35,383 EPOCH 132 done: loss 0.0712 - lr 0.000781 |
|
2022-11-06 23:03:45,044 Evaluating as a multi-label problem: False |
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2022-11-06 23:03:45,159 TEST : loss 0.07832777500152588 - f1-score (micro avg) 0.9793 |
|
2022-11-06 23:03:45,272 Epoch 132: reducing learning rate of group 0 to 3.9063e-04. |
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2022-11-06 23:03:45,273 BAD EPOCHS (no improvement): 4 |
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2022-11-06 23:03:45,481 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 23:03:51,549 epoch 133 - iter 38/386 - loss 0.07133258 - samples/sec: 100.26 - lr: 0.000391 |
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2022-11-06 23:03:57,506 epoch 133 - iter 76/386 - loss 0.07133234 - samples/sec: 102.12 - lr: 0.000391 |
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2022-11-06 23:04:03,027 epoch 133 - iter 114/386 - loss 0.07265932 - samples/sec: 110.20 - lr: 0.000391 |
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2022-11-06 23:04:08,538 epoch 133 - iter 152/386 - loss 0.07271682 - samples/sec: 110.38 - lr: 0.000391 |
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2022-11-06 23:04:14,070 epoch 133 - iter 190/386 - loss 0.07173817 - samples/sec: 109.97 - lr: 0.000391 |
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2022-11-06 23:04:19,366 epoch 133 - iter 228/386 - loss 0.07111288 - samples/sec: 114.87 - lr: 0.000391 |
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2022-11-06 23:04:24,572 epoch 133 - iter 266/386 - loss 0.07163658 - samples/sec: 116.86 - lr: 0.000391 |
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2022-11-06 23:04:30,386 epoch 133 - iter 304/386 - loss 0.07191561 - samples/sec: 104.63 - lr: 0.000391 |
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2022-11-06 23:04:35,605 epoch 133 - iter 342/386 - loss 0.07226248 - samples/sec: 116.57 - lr: 0.000391 |
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2022-11-06 23:04:41,353 epoch 133 - iter 380/386 - loss 0.07225441 - samples/sec: 105.83 - lr: 0.000391 |
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2022-11-06 23:04:42,215 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 23:04:42,215 EPOCH 133 done: loss 0.0724 - lr 0.000391 |
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2022-11-06 23:04:51,832 Evaluating as a multi-label problem: False |
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2022-11-06 23:04:51,947 TEST : loss 0.07831750810146332 - f1-score (micro avg) 0.9792 |
|
2022-11-06 23:04:52,060 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 23:04:52,265 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 23:04:57,502 epoch 134 - iter 38/386 - loss 0.07272210 - samples/sec: 116.20 - lr: 0.000391 |
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2022-11-06 23:05:03,859 epoch 134 - iter 76/386 - loss 0.07188465 - samples/sec: 95.69 - lr: 0.000391 |
|
2022-11-06 23:05:09,578 epoch 134 - iter 114/386 - loss 0.07221689 - samples/sec: 106.38 - lr: 0.000391 |
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2022-11-06 23:05:14,935 epoch 134 - iter 152/386 - loss 0.07164910 - samples/sec: 113.54 - lr: 0.000391 |
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2022-11-06 23:05:20,362 epoch 134 - iter 190/386 - loss 0.07186012 - samples/sec: 112.11 - lr: 0.000391 |
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2022-11-06 23:05:25,922 epoch 134 - iter 228/386 - loss 0.07095586 - samples/sec: 109.41 - lr: 0.000391 |
|
2022-11-06 23:05:31,321 epoch 134 - iter 266/386 - loss 0.07005834 - samples/sec: 112.67 - lr: 0.000391 |
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2022-11-06 23:05:36,532 epoch 134 - iter 304/386 - loss 0.06974718 - samples/sec: 116.76 - lr: 0.000391 |
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2022-11-06 23:05:41,664 epoch 134 - iter 342/386 - loss 0.07038373 - samples/sec: 118.55 - lr: 0.000391 |
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2022-11-06 23:05:47,300 epoch 134 - iter 380/386 - loss 0.07138653 - samples/sec: 107.94 - lr: 0.000391 |
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2022-11-06 23:05:48,096 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 23:05:48,096 EPOCH 134 done: loss 0.0713 - lr 0.000391 |
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2022-11-06 23:05:57,677 Evaluating as a multi-label problem: False |
|
2022-11-06 23:05:57,792 TEST : loss 0.07832799106836319 - f1-score (micro avg) 0.9793 |
|
2022-11-06 23:05:57,905 BAD EPOCHS (no improvement): 2 |
|
2022-11-06 23:05:58,112 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 23:06:03,825 epoch 135 - iter 38/386 - loss 0.07625152 - samples/sec: 106.50 - lr: 0.000391 |
|
2022-11-06 23:06:09,420 epoch 135 - iter 76/386 - loss 0.07596756 - samples/sec: 108.74 - lr: 0.000391 |
|
2022-11-06 23:06:14,938 epoch 135 - iter 114/386 - loss 0.07537203 - samples/sec: 110.23 - lr: 0.000391 |
|
2022-11-06 23:06:20,851 epoch 135 - iter 152/386 - loss 0.07465357 - samples/sec: 102.88 - lr: 0.000391 |
|
2022-11-06 23:06:26,437 epoch 135 - iter 190/386 - loss 0.07282803 - samples/sec: 108.92 - lr: 0.000391 |
|
2022-11-06 23:06:32,254 epoch 135 - iter 228/386 - loss 0.07223191 - samples/sec: 104.57 - lr: 0.000391 |
|
2022-11-06 23:06:37,417 epoch 135 - iter 266/386 - loss 0.07261668 - samples/sec: 117.82 - lr: 0.000391 |
|
2022-11-06 23:06:43,327 epoch 135 - iter 304/386 - loss 0.07227402 - samples/sec: 102.93 - lr: 0.000391 |
|
2022-11-06 23:06:48,605 epoch 135 - iter 342/386 - loss 0.07149145 - samples/sec: 115.28 - lr: 0.000391 |
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2022-11-06 23:06:53,388 epoch 135 - iter 380/386 - loss 0.07197639 - samples/sec: 127.19 - lr: 0.000391 |
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2022-11-06 23:06:54,256 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 23:06:54,256 EPOCH 135 done: loss 0.0719 - lr 0.000391 |
|
2022-11-06 23:07:03,834 Evaluating as a multi-label problem: False |
|
2022-11-06 23:07:03,950 TEST : loss 0.07829069346189499 - f1-score (micro avg) 0.9793 |
|
2022-11-06 23:07:04,062 BAD EPOCHS (no improvement): 3 |
|
2022-11-06 23:07:04,267 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 23:07:09,727 epoch 136 - iter 38/386 - loss 0.07134941 - samples/sec: 111.46 - lr: 0.000391 |
|
2022-11-06 23:07:15,291 epoch 136 - iter 76/386 - loss 0.07170014 - samples/sec: 109.33 - lr: 0.000391 |
|
2022-11-06 23:07:21,563 epoch 136 - iter 114/386 - loss 0.07030659 - samples/sec: 96.99 - lr: 0.000391 |
|
2022-11-06 23:07:27,126 epoch 136 - iter 152/386 - loss 0.07200756 - samples/sec: 109.34 - lr: 0.000391 |
|
2022-11-06 23:07:32,758 epoch 136 - iter 190/386 - loss 0.07243107 - samples/sec: 108.02 - lr: 0.000391 |
|
2022-11-06 23:07:38,121 epoch 136 - iter 228/386 - loss 0.07266476 - samples/sec: 113.44 - lr: 0.000391 |
|
2022-11-06 23:07:43,764 epoch 136 - iter 266/386 - loss 0.07246653 - samples/sec: 107.81 - lr: 0.000391 |
|
2022-11-06 23:07:49,451 epoch 136 - iter 304/386 - loss 0.07247297 - samples/sec: 106.96 - lr: 0.000391 |
|
2022-11-06 23:07:55,084 epoch 136 - iter 342/386 - loss 0.07289621 - samples/sec: 107.99 - lr: 0.000391 |
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2022-11-06 23:08:00,375 epoch 136 - iter 380/386 - loss 0.07291326 - samples/sec: 115.00 - lr: 0.000391 |
|
2022-11-06 23:08:01,172 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 23:08:01,172 EPOCH 136 done: loss 0.0726 - lr 0.000391 |
|
2022-11-06 23:08:10,258 Evaluating as a multi-label problem: False |
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2022-11-06 23:08:10,372 TEST : loss 0.07828548550605774 - f1-score (micro avg) 0.9793 |
|
2022-11-06 23:08:10,485 Epoch 136: reducing learning rate of group 0 to 1.9531e-04. |
|
2022-11-06 23:08:10,486 BAD EPOCHS (no improvement): 4 |
|
2022-11-06 23:08:10,684 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 23:08:16,120 epoch 137 - iter 38/386 - loss 0.07268823 - samples/sec: 111.92 - lr: 0.000195 |
|
2022-11-06 23:08:21,492 epoch 137 - iter 76/386 - loss 0.07101301 - samples/sec: 113.26 - lr: 0.000195 |
|
2022-11-06 23:08:26,957 epoch 137 - iter 114/386 - loss 0.06977042 - samples/sec: 111.31 - lr: 0.000195 |
|
2022-11-06 23:08:32,736 epoch 137 - iter 152/386 - loss 0.07180263 - samples/sec: 105.27 - lr: 0.000195 |
|
2022-11-06 23:08:38,291 epoch 137 - iter 190/386 - loss 0.07341440 - samples/sec: 109.51 - lr: 0.000195 |
|
2022-11-06 23:08:43,944 epoch 137 - iter 228/386 - loss 0.07287976 - samples/sec: 107.61 - lr: 0.000195 |
|
2022-11-06 23:08:49,582 epoch 137 - iter 266/386 - loss 0.07302229 - samples/sec: 107.91 - lr: 0.000195 |
|
2022-11-06 23:08:55,206 epoch 137 - iter 304/386 - loss 0.07313939 - samples/sec: 108.17 - lr: 0.000195 |
|
2022-11-06 23:09:01,352 epoch 137 - iter 342/386 - loss 0.07256527 - samples/sec: 98.97 - lr: 0.000195 |
|
2022-11-06 23:09:07,148 epoch 137 - iter 380/386 - loss 0.07234924 - samples/sec: 104.95 - lr: 0.000195 |
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2022-11-06 23:09:07,904 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 23:09:07,904 EPOCH 137 done: loss 0.0723 - lr 0.000195 |
|
2022-11-06 23:09:17,011 Evaluating as a multi-label problem: False |
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2022-11-06 23:09:17,126 TEST : loss 0.07833118736743927 - f1-score (micro avg) 0.9793 |
|
2022-11-06 23:09:17,239 BAD EPOCHS (no improvement): 1 |
|
2022-11-06 23:09:17,437 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 23:09:23,143 epoch 138 - iter 38/386 - loss 0.07121465 - samples/sec: 106.64 - lr: 0.000195 |
|
2022-11-06 23:09:28,758 epoch 138 - iter 76/386 - loss 0.07053113 - samples/sec: 108.34 - lr: 0.000195 |
|
2022-11-06 23:09:34,135 epoch 138 - iter 114/386 - loss 0.07217032 - samples/sec: 113.14 - lr: 0.000195 |
|
2022-11-06 23:09:39,673 epoch 138 - iter 152/386 - loss 0.07049193 - samples/sec: 109.84 - lr: 0.000195 |
|
2022-11-06 23:09:45,545 epoch 138 - iter 190/386 - loss 0.07228868 - samples/sec: 103.61 - lr: 0.000195 |
|
2022-11-06 23:09:51,097 epoch 138 - iter 228/386 - loss 0.07213669 - samples/sec: 109.56 - lr: 0.000195 |
|
2022-11-06 23:09:56,773 epoch 138 - iter 266/386 - loss 0.07246026 - samples/sec: 107.17 - lr: 0.000195 |
|
2022-11-06 23:10:02,194 epoch 138 - iter 304/386 - loss 0.07150123 - samples/sec: 112.22 - lr: 0.000195 |
|
2022-11-06 23:10:07,597 epoch 138 - iter 342/386 - loss 0.07211538 - samples/sec: 112.60 - lr: 0.000195 |
|
2022-11-06 23:10:13,032 epoch 138 - iter 380/386 - loss 0.07293704 - samples/sec: 111.93 - lr: 0.000195 |
|
2022-11-06 23:10:13,786 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 23:10:13,786 EPOCH 138 done: loss 0.0726 - lr 0.000195 |
|
2022-11-06 23:10:25,774 Evaluating as a multi-label problem: False |
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2022-11-06 23:10:25,889 TEST : loss 0.07832229882478714 - f1-score (micro avg) 0.9792 |
|
2022-11-06 23:10:26,002 BAD EPOCHS (no improvement): 2 |
|
2022-11-06 23:10:26,210 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 23:10:31,431 epoch 139 - iter 38/386 - loss 0.07244392 - samples/sec: 116.55 - lr: 0.000195 |
|
2022-11-06 23:10:36,809 epoch 139 - iter 76/386 - loss 0.06971478 - samples/sec: 113.11 - lr: 0.000195 |
|
2022-11-06 23:10:42,330 epoch 139 - iter 114/386 - loss 0.06955680 - samples/sec: 110.18 - lr: 0.000195 |
|
2022-11-06 23:10:47,907 epoch 139 - iter 152/386 - loss 0.07193651 - samples/sec: 109.09 - lr: 0.000195 |
|
2022-11-06 23:10:53,595 epoch 139 - iter 190/386 - loss 0.07346354 - samples/sec: 106.96 - lr: 0.000195 |
|
2022-11-06 23:10:59,145 epoch 139 - iter 228/386 - loss 0.07351255 - samples/sec: 109.60 - lr: 0.000195 |
|
2022-11-06 23:11:04,574 epoch 139 - iter 266/386 - loss 0.07280062 - samples/sec: 112.06 - lr: 0.000195 |
|
2022-11-06 23:11:10,865 epoch 139 - iter 304/386 - loss 0.07154111 - samples/sec: 96.69 - lr: 0.000195 |
|
2022-11-06 23:11:16,382 epoch 139 - iter 342/386 - loss 0.07190465 - samples/sec: 110.27 - lr: 0.000195 |
|
2022-11-06 23:11:21,840 epoch 139 - iter 380/386 - loss 0.07176361 - samples/sec: 111.46 - lr: 0.000195 |
|
2022-11-06 23:11:22,626 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 23:11:22,626 EPOCH 139 done: loss 0.0717 - lr 0.000195 |
|
2022-11-06 23:11:32,319 Evaluating as a multi-label problem: False |
|
2022-11-06 23:11:32,434 TEST : loss 0.07830418646335602 - f1-score (micro avg) 0.9792 |
|
2022-11-06 23:11:32,547 BAD EPOCHS (no improvement): 3 |
|
2022-11-06 23:11:32,756 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 23:11:38,308 epoch 140 - iter 38/386 - loss 0.07596932 - samples/sec: 109.59 - lr: 0.000195 |
|
2022-11-06 23:11:43,612 epoch 140 - iter 76/386 - loss 0.07530102 - samples/sec: 114.70 - lr: 0.000195 |
|
2022-11-06 23:11:48,989 epoch 140 - iter 114/386 - loss 0.07424606 - samples/sec: 113.14 - lr: 0.000195 |
|
2022-11-06 23:11:54,700 epoch 140 - iter 152/386 - loss 0.07306686 - samples/sec: 106.52 - lr: 0.000195 |
|
2022-11-06 23:12:00,523 epoch 140 - iter 190/386 - loss 0.07428603 - samples/sec: 104.47 - lr: 0.000195 |
|
2022-11-06 23:12:05,472 epoch 140 - iter 228/386 - loss 0.07433713 - samples/sec: 122.93 - lr: 0.000195 |
|
2022-11-06 23:12:11,266 epoch 140 - iter 266/386 - loss 0.07343813 - samples/sec: 105.00 - lr: 0.000195 |
|
2022-11-06 23:12:17,102 epoch 140 - iter 304/386 - loss 0.07382207 - samples/sec: 104.24 - lr: 0.000195 |
|
2022-11-06 23:12:22,701 epoch 140 - iter 342/386 - loss 0.07336550 - samples/sec: 108.65 - lr: 0.000195 |
|
2022-11-06 23:12:28,060 epoch 140 - iter 380/386 - loss 0.07330513 - samples/sec: 113.51 - lr: 0.000195 |
|
2022-11-06 23:12:28,798 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 23:12:28,798 EPOCH 140 done: loss 0.0733 - lr 0.000195 |
|
2022-11-06 23:12:38,412 Evaluating as a multi-label problem: False |
|
2022-11-06 23:12:38,528 TEST : loss 0.07832666486501694 - f1-score (micro avg) 0.9793 |
|
2022-11-06 23:12:38,641 Epoch 140: reducing learning rate of group 0 to 9.7656e-05. |
|
2022-11-06 23:12:38,641 BAD EPOCHS (no improvement): 4 |
|
2022-11-06 23:12:38,846 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 23:12:38,846 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 23:12:38,846 learning rate too small - quitting training! |
|
2022-11-06 23:12:38,846 ---------------------------------------------------------------------------------------------------- |
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2022-11-06 23:12:38,988 ---------------------------------------------------------------------------------------------------- |
|
2022-11-06 23:12:38,988 Testing using last state of model ... |
|
2022-11-06 23:12:48,641 Evaluating as a multi-label problem: False |
|
2022-11-06 23:12:48,755 0.9793 0.9793 0.9793 0.9793 |
|
2022-11-06 23:12:48,755 |
|
Results: |
|
- F-score (micro) 0.9793 |
|
- F-score (macro) 0.9275 |
|
- Accuracy 0.9793 |
|
|
|
By class: |
|
precision recall f1-score support |
|
|
|
NOUN 0.9857 0.9851 0.9854 4549 |
|
PUNCT 0.9984 1.0000 0.9992 3097 |
|
ADJ 0.9772 0.9852 0.9812 1959 |
|
ADP 0.9956 0.9968 0.9962 1584 |
|
VERB 0.9891 0.9910 0.9900 1552 |
|
ADV 0.9630 0.9118 0.9367 714 |
|
CCONJ 0.9685 0.9746 0.9715 630 |
|
PROPN 0.9279 0.9472 0.9375 625 |
|
DET 0.9729 0.9698 0.9713 629 |
|
PRON 0.9706 0.9631 0.9669 515 |
|
PART 0.9235 0.8693 0.8956 375 |
|
NUM 0.9722 0.9804 0.9763 357 |
|
SCONJ 0.8768 0.9577 0.9154 260 |
|
AUX 0.8906 0.9500 0.9194 120 |
|
X 0.9833 0.9593 0.9712 123 |
|
SYM 1.0000 0.7059 0.8276 17 |
|
INTJ 0.5556 0.5000 0.5263 10 |
|
|
|
accuracy 0.9793 17116 |
|
macro avg 0.9383 0.9204 0.9275 17116 |
|
weighted avg 0.9794 0.9793 0.9792 17116 |
|
|
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2022-11-06 23:12:48,755 ---------------------------------------------------------------------------------------------------- |
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