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2023-10-17 15:20:15,009 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:20:15,010 Model: "SequenceTagger( |
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(embeddings): TransformerWordEmbeddings( |
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(model): ElectraModel( |
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(embeddings): ElectraEmbeddings( |
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(word_embeddings): Embedding(32001, 768) |
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(position_embeddings): Embedding(512, 768) |
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(token_type_embeddings): Embedding(2, 768) |
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(LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) |
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(dropout): Dropout(p=0.1, inplace=False) |
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) |
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(encoder): ElectraEncoder( |
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(layer): ModuleList( |
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(0-11): 12 x ElectraLayer( |
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(attention): ElectraAttention( |
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(self): ElectraSelfAttention( |
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(query): Linear(in_features=768, out_features=768, bias=True) |
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(key): Linear(in_features=768, out_features=768, bias=True) |
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(value): Linear(in_features=768, out_features=768, bias=True) |
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(dropout): Dropout(p=0.1, inplace=False) |
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) |
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(output): ElectraSelfOutput( |
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(dense): Linear(in_features=768, out_features=768, bias=True) |
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(LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) |
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(dropout): Dropout(p=0.1, inplace=False) |
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) |
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) |
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(intermediate): ElectraIntermediate( |
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(dense): Linear(in_features=768, out_features=3072, bias=True) |
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(intermediate_act_fn): GELUActivation() |
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) |
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(output): ElectraOutput( |
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(dense): Linear(in_features=3072, out_features=768, bias=True) |
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(LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) |
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(dropout): Dropout(p=0.1, inplace=False) |
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) |
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) |
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) |
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) |
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) |
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) |
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(locked_dropout): LockedDropout(p=0.5) |
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(linear): Linear(in_features=768, out_features=13, bias=True) |
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(loss_function): CrossEntropyLoss() |
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)" |
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2023-10-17 15:20:15,010 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:20:15,010 MultiCorpus: 5777 train + 722 dev + 723 test sentences |
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- NER_ICDAR_EUROPEANA Corpus: 5777 train + 722 dev + 723 test sentences - /root/.flair/datasets/ner_icdar_europeana/nl |
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2023-10-17 15:20:15,010 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:20:15,010 Train: 5777 sentences |
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2023-10-17 15:20:15,011 (train_with_dev=False, train_with_test=False) |
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2023-10-17 15:20:15,011 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:20:15,011 Training Params: |
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2023-10-17 15:20:15,011 - learning_rate: "3e-05" |
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2023-10-17 15:20:15,011 - mini_batch_size: "4" |
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2023-10-17 15:20:15,011 - max_epochs: "10" |
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2023-10-17 15:20:15,011 - shuffle: "True" |
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2023-10-17 15:20:15,011 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:20:15,011 Plugins: |
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2023-10-17 15:20:15,011 - TensorboardLogger |
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2023-10-17 15:20:15,011 - LinearScheduler | warmup_fraction: '0.1' |
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2023-10-17 15:20:15,011 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:20:15,011 Final evaluation on model from best epoch (best-model.pt) |
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2023-10-17 15:20:15,011 - metric: "('micro avg', 'f1-score')" |
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2023-10-17 15:20:15,011 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:20:15,011 Computation: |
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2023-10-17 15:20:15,011 - compute on device: cuda:0 |
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2023-10-17 15:20:15,011 - embedding storage: none |
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2023-10-17 15:20:15,011 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:20:15,011 Model training base path: "hmbench-icdar/nl-hmteams/teams-base-historic-multilingual-discriminator-bs4-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-1" |
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2023-10-17 15:20:15,011 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:20:15,011 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:20:15,011 Logging anything other than scalars to TensorBoard is currently not supported. |
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2023-10-17 15:20:23,073 epoch 1 - iter 144/1445 - loss 2.33324949 - time (sec): 8.06 - samples/sec: 2302.06 - lr: 0.000003 - momentum: 0.000000 |
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2023-10-17 15:20:30,031 epoch 1 - iter 288/1445 - loss 1.40669834 - time (sec): 15.02 - samples/sec: 2293.24 - lr: 0.000006 - momentum: 0.000000 |
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2023-10-17 15:20:37,277 epoch 1 - iter 432/1445 - loss 0.99311609 - time (sec): 22.26 - samples/sec: 2340.14 - lr: 0.000009 - momentum: 0.000000 |
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2023-10-17 15:20:44,228 epoch 1 - iter 576/1445 - loss 0.79532458 - time (sec): 29.22 - samples/sec: 2337.21 - lr: 0.000012 - momentum: 0.000000 |
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2023-10-17 15:20:51,036 epoch 1 - iter 720/1445 - loss 0.66249281 - time (sec): 36.02 - samples/sec: 2401.24 - lr: 0.000015 - momentum: 0.000000 |
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2023-10-17 15:20:58,193 epoch 1 - iter 864/1445 - loss 0.56791320 - time (sec): 43.18 - samples/sec: 2443.46 - lr: 0.000018 - momentum: 0.000000 |
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2023-10-17 15:21:05,065 epoch 1 - iter 1008/1445 - loss 0.50430390 - time (sec): 50.05 - samples/sec: 2460.17 - lr: 0.000021 - momentum: 0.000000 |
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2023-10-17 15:21:12,157 epoch 1 - iter 1152/1445 - loss 0.45583800 - time (sec): 57.14 - samples/sec: 2469.61 - lr: 0.000024 - momentum: 0.000000 |
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2023-10-17 15:21:19,146 epoch 1 - iter 1296/1445 - loss 0.42025604 - time (sec): 64.13 - samples/sec: 2471.73 - lr: 0.000027 - momentum: 0.000000 |
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2023-10-17 15:21:26,123 epoch 1 - iter 1440/1445 - loss 0.39100512 - time (sec): 71.11 - samples/sec: 2470.36 - lr: 0.000030 - momentum: 0.000000 |
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2023-10-17 15:21:26,351 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:21:26,351 EPOCH 1 done: loss 0.3901 - lr: 0.000030 |
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2023-10-17 15:21:29,006 DEV : loss 0.1134478896856308 - f1-score (micro avg) 0.6988 |
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2023-10-17 15:21:29,021 saving best model |
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2023-10-17 15:21:29,419 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:21:36,099 epoch 2 - iter 144/1445 - loss 0.11423400 - time (sec): 6.68 - samples/sec: 2491.07 - lr: 0.000030 - momentum: 0.000000 |
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2023-10-17 15:21:42,808 epoch 2 - iter 288/1445 - loss 0.11006024 - time (sec): 13.39 - samples/sec: 2534.73 - lr: 0.000029 - momentum: 0.000000 |
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2023-10-17 15:21:49,527 epoch 2 - iter 432/1445 - loss 0.10104983 - time (sec): 20.11 - samples/sec: 2552.67 - lr: 0.000029 - momentum: 0.000000 |
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2023-10-17 15:21:56,423 epoch 2 - iter 576/1445 - loss 0.09617376 - time (sec): 27.00 - samples/sec: 2535.33 - lr: 0.000029 - momentum: 0.000000 |
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2023-10-17 15:22:03,695 epoch 2 - iter 720/1445 - loss 0.09369082 - time (sec): 34.27 - samples/sec: 2531.86 - lr: 0.000028 - momentum: 0.000000 |
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2023-10-17 15:22:11,248 epoch 2 - iter 864/1445 - loss 0.09042169 - time (sec): 41.83 - samples/sec: 2531.47 - lr: 0.000028 - momentum: 0.000000 |
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2023-10-17 15:22:18,355 epoch 2 - iter 1008/1445 - loss 0.09025166 - time (sec): 48.93 - samples/sec: 2507.99 - lr: 0.000028 - momentum: 0.000000 |
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2023-10-17 15:22:25,543 epoch 2 - iter 1152/1445 - loss 0.09048999 - time (sec): 56.12 - samples/sec: 2502.98 - lr: 0.000027 - momentum: 0.000000 |
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2023-10-17 15:22:32,470 epoch 2 - iter 1296/1445 - loss 0.09136875 - time (sec): 63.05 - samples/sec: 2497.21 - lr: 0.000027 - momentum: 0.000000 |
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2023-10-17 15:22:39,747 epoch 2 - iter 1440/1445 - loss 0.09254084 - time (sec): 70.33 - samples/sec: 2499.02 - lr: 0.000027 - momentum: 0.000000 |
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2023-10-17 15:22:39,976 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:22:39,977 EPOCH 2 done: loss 0.0928 - lr: 0.000027 |
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2023-10-17 15:22:43,507 DEV : loss 0.09797008335590363 - f1-score (micro avg) 0.7636 |
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2023-10-17 15:22:43,523 saving best model |
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2023-10-17 15:22:44,069 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:22:51,178 epoch 3 - iter 144/1445 - loss 0.07299256 - time (sec): 7.11 - samples/sec: 2444.22 - lr: 0.000026 - momentum: 0.000000 |
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2023-10-17 15:22:57,977 epoch 3 - iter 288/1445 - loss 0.06634279 - time (sec): 13.91 - samples/sec: 2490.30 - lr: 0.000026 - momentum: 0.000000 |
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2023-10-17 15:23:05,074 epoch 3 - iter 432/1445 - loss 0.06581683 - time (sec): 21.00 - samples/sec: 2551.84 - lr: 0.000026 - momentum: 0.000000 |
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2023-10-17 15:23:11,936 epoch 3 - iter 576/1445 - loss 0.07201697 - time (sec): 27.87 - samples/sec: 2538.19 - lr: 0.000025 - momentum: 0.000000 |
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2023-10-17 15:23:18,903 epoch 3 - iter 720/1445 - loss 0.07104181 - time (sec): 34.83 - samples/sec: 2511.65 - lr: 0.000025 - momentum: 0.000000 |
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2023-10-17 15:23:25,927 epoch 3 - iter 864/1445 - loss 0.07023237 - time (sec): 41.86 - samples/sec: 2516.01 - lr: 0.000025 - momentum: 0.000000 |
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2023-10-17 15:23:33,061 epoch 3 - iter 1008/1445 - loss 0.06913832 - time (sec): 48.99 - samples/sec: 2490.96 - lr: 0.000024 - momentum: 0.000000 |
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2023-10-17 15:23:40,153 epoch 3 - iter 1152/1445 - loss 0.06852697 - time (sec): 56.08 - samples/sec: 2486.94 - lr: 0.000024 - momentum: 0.000000 |
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2023-10-17 15:23:47,600 epoch 3 - iter 1296/1445 - loss 0.06920774 - time (sec): 63.53 - samples/sec: 2481.25 - lr: 0.000024 - momentum: 0.000000 |
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2023-10-17 15:23:54,842 epoch 3 - iter 1440/1445 - loss 0.06776713 - time (sec): 70.77 - samples/sec: 2483.99 - lr: 0.000023 - momentum: 0.000000 |
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2023-10-17 15:23:55,074 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:23:55,074 EPOCH 3 done: loss 0.0679 - lr: 0.000023 |
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2023-10-17 15:23:58,305 DEV : loss 0.07238871604204178 - f1-score (micro avg) 0.8599 |
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2023-10-17 15:23:58,320 saving best model |
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2023-10-17 15:23:58,869 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:24:05,938 epoch 4 - iter 144/1445 - loss 0.03825652 - time (sec): 7.07 - samples/sec: 2582.66 - lr: 0.000023 - momentum: 0.000000 |
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2023-10-17 15:24:13,011 epoch 4 - iter 288/1445 - loss 0.05121297 - time (sec): 14.14 - samples/sec: 2515.02 - lr: 0.000023 - momentum: 0.000000 |
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2023-10-17 15:24:20,248 epoch 4 - iter 432/1445 - loss 0.04707007 - time (sec): 21.38 - samples/sec: 2475.52 - lr: 0.000022 - momentum: 0.000000 |
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2023-10-17 15:24:27,099 epoch 4 - iter 576/1445 - loss 0.04864143 - time (sec): 28.23 - samples/sec: 2490.67 - lr: 0.000022 - momentum: 0.000000 |
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2023-10-17 15:24:34,071 epoch 4 - iter 720/1445 - loss 0.05041580 - time (sec): 35.20 - samples/sec: 2469.04 - lr: 0.000022 - momentum: 0.000000 |
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2023-10-17 15:24:41,242 epoch 4 - iter 864/1445 - loss 0.05057361 - time (sec): 42.37 - samples/sec: 2466.87 - lr: 0.000021 - momentum: 0.000000 |
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2023-10-17 15:24:48,213 epoch 4 - iter 1008/1445 - loss 0.04981836 - time (sec): 49.34 - samples/sec: 2478.95 - lr: 0.000021 - momentum: 0.000000 |
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2023-10-17 15:24:54,867 epoch 4 - iter 1152/1445 - loss 0.05022101 - time (sec): 56.00 - samples/sec: 2498.44 - lr: 0.000021 - momentum: 0.000000 |
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2023-10-17 15:25:01,564 epoch 4 - iter 1296/1445 - loss 0.05005487 - time (sec): 62.69 - samples/sec: 2514.15 - lr: 0.000020 - momentum: 0.000000 |
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2023-10-17 15:25:08,655 epoch 4 - iter 1440/1445 - loss 0.05140703 - time (sec): 69.78 - samples/sec: 2519.10 - lr: 0.000020 - momentum: 0.000000 |
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2023-10-17 15:25:08,886 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:25:08,886 EPOCH 4 done: loss 0.0513 - lr: 0.000020 |
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2023-10-17 15:25:12,521 DEV : loss 0.08748035877943039 - f1-score (micro avg) 0.8513 |
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2023-10-17 15:25:12,536 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:25:20,019 epoch 5 - iter 144/1445 - loss 0.02484292 - time (sec): 7.48 - samples/sec: 2365.34 - lr: 0.000020 - momentum: 0.000000 |
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2023-10-17 15:25:27,347 epoch 5 - iter 288/1445 - loss 0.02639251 - time (sec): 14.81 - samples/sec: 2426.84 - lr: 0.000019 - momentum: 0.000000 |
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2023-10-17 15:25:34,576 epoch 5 - iter 432/1445 - loss 0.03062150 - time (sec): 22.04 - samples/sec: 2438.65 - lr: 0.000019 - momentum: 0.000000 |
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2023-10-17 15:25:41,500 epoch 5 - iter 576/1445 - loss 0.03478141 - time (sec): 28.96 - samples/sec: 2433.14 - lr: 0.000019 - momentum: 0.000000 |
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2023-10-17 15:25:48,647 epoch 5 - iter 720/1445 - loss 0.03435012 - time (sec): 36.11 - samples/sec: 2431.81 - lr: 0.000018 - momentum: 0.000000 |
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2023-10-17 15:25:55,712 epoch 5 - iter 864/1445 - loss 0.03915073 - time (sec): 43.17 - samples/sec: 2429.56 - lr: 0.000018 - momentum: 0.000000 |
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2023-10-17 15:26:02,874 epoch 5 - iter 1008/1445 - loss 0.04019423 - time (sec): 50.34 - samples/sec: 2424.89 - lr: 0.000018 - momentum: 0.000000 |
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2023-10-17 15:26:09,941 epoch 5 - iter 1152/1445 - loss 0.04137874 - time (sec): 57.40 - samples/sec: 2449.49 - lr: 0.000017 - momentum: 0.000000 |
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2023-10-17 15:26:16,823 epoch 5 - iter 1296/1445 - loss 0.04231658 - time (sec): 64.29 - samples/sec: 2455.18 - lr: 0.000017 - momentum: 0.000000 |
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2023-10-17 15:26:24,165 epoch 5 - iter 1440/1445 - loss 0.04229848 - time (sec): 71.63 - samples/sec: 2452.34 - lr: 0.000017 - momentum: 0.000000 |
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2023-10-17 15:26:24,411 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:26:24,411 EPOCH 5 done: loss 0.0423 - lr: 0.000017 |
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2023-10-17 15:26:27,792 DEV : loss 0.11643949151039124 - f1-score (micro avg) 0.7813 |
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2023-10-17 15:26:27,810 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:26:35,160 epoch 6 - iter 144/1445 - loss 0.04407312 - time (sec): 7.35 - samples/sec: 2381.66 - lr: 0.000016 - momentum: 0.000000 |
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2023-10-17 15:26:42,213 epoch 6 - iter 288/1445 - loss 0.07041699 - time (sec): 14.40 - samples/sec: 2363.33 - lr: 0.000016 - momentum: 0.000000 |
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2023-10-17 15:26:49,199 epoch 6 - iter 432/1445 - loss 0.06543099 - time (sec): 21.39 - samples/sec: 2412.35 - lr: 0.000016 - momentum: 0.000000 |
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2023-10-17 15:26:56,329 epoch 6 - iter 576/1445 - loss 0.05494049 - time (sec): 28.52 - samples/sec: 2447.24 - lr: 0.000015 - momentum: 0.000000 |
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2023-10-17 15:27:03,461 epoch 6 - iter 720/1445 - loss 0.05313692 - time (sec): 35.65 - samples/sec: 2468.33 - lr: 0.000015 - momentum: 0.000000 |
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2023-10-17 15:27:10,213 epoch 6 - iter 864/1445 - loss 0.04946118 - time (sec): 42.40 - samples/sec: 2462.88 - lr: 0.000015 - momentum: 0.000000 |
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2023-10-17 15:27:16,992 epoch 6 - iter 1008/1445 - loss 0.04715937 - time (sec): 49.18 - samples/sec: 2492.01 - lr: 0.000014 - momentum: 0.000000 |
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2023-10-17 15:27:23,900 epoch 6 - iter 1152/1445 - loss 0.04549664 - time (sec): 56.09 - samples/sec: 2479.47 - lr: 0.000014 - momentum: 0.000000 |
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2023-10-17 15:27:30,845 epoch 6 - iter 1296/1445 - loss 0.04407099 - time (sec): 63.03 - samples/sec: 2486.69 - lr: 0.000014 - momentum: 0.000000 |
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2023-10-17 15:27:37,799 epoch 6 - iter 1440/1445 - loss 0.04231390 - time (sec): 69.99 - samples/sec: 2507.53 - lr: 0.000013 - momentum: 0.000000 |
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2023-10-17 15:27:38,026 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:27:38,026 EPOCH 6 done: loss 0.0422 - lr: 0.000013 |
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2023-10-17 15:27:41,262 DEV : loss 0.12753015756607056 - f1-score (micro avg) 0.8179 |
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2023-10-17 15:27:41,277 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:27:48,074 epoch 7 - iter 144/1445 - loss 0.02864804 - time (sec): 6.80 - samples/sec: 2541.40 - lr: 0.000013 - momentum: 0.000000 |
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2023-10-17 15:27:54,732 epoch 7 - iter 288/1445 - loss 0.02850202 - time (sec): 13.45 - samples/sec: 2529.29 - lr: 0.000013 - momentum: 0.000000 |
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2023-10-17 15:28:01,745 epoch 7 - iter 432/1445 - loss 0.02700154 - time (sec): 20.47 - samples/sec: 2538.36 - lr: 0.000012 - momentum: 0.000000 |
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2023-10-17 15:28:09,285 epoch 7 - iter 576/1445 - loss 0.02685090 - time (sec): 28.01 - samples/sec: 2500.37 - lr: 0.000012 - momentum: 0.000000 |
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2023-10-17 15:28:16,228 epoch 7 - iter 720/1445 - loss 0.02631576 - time (sec): 34.95 - samples/sec: 2498.86 - lr: 0.000012 - momentum: 0.000000 |
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2023-10-17 15:28:23,229 epoch 7 - iter 864/1445 - loss 0.02503229 - time (sec): 41.95 - samples/sec: 2527.10 - lr: 0.000011 - momentum: 0.000000 |
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2023-10-17 15:28:30,267 epoch 7 - iter 1008/1445 - loss 0.02322476 - time (sec): 48.99 - samples/sec: 2513.53 - lr: 0.000011 - momentum: 0.000000 |
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2023-10-17 15:28:37,208 epoch 7 - iter 1152/1445 - loss 0.02262618 - time (sec): 55.93 - samples/sec: 2507.14 - lr: 0.000011 - momentum: 0.000000 |
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2023-10-17 15:28:44,333 epoch 7 - iter 1296/1445 - loss 0.02359839 - time (sec): 63.05 - samples/sec: 2507.22 - lr: 0.000010 - momentum: 0.000000 |
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2023-10-17 15:28:51,234 epoch 7 - iter 1440/1445 - loss 0.02410498 - time (sec): 69.96 - samples/sec: 2512.80 - lr: 0.000010 - momentum: 0.000000 |
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2023-10-17 15:28:51,455 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:28:51,456 EPOCH 7 done: loss 0.0241 - lr: 0.000010 |
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2023-10-17 15:28:54,762 DEV : loss 0.13132773339748383 - f1-score (micro avg) 0.8242 |
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2023-10-17 15:28:54,780 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:29:01,739 epoch 8 - iter 144/1445 - loss 0.02599645 - time (sec): 6.96 - samples/sec: 2320.98 - lr: 0.000010 - momentum: 0.000000 |
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2023-10-17 15:29:09,413 epoch 8 - iter 288/1445 - loss 0.03908539 - time (sec): 14.63 - samples/sec: 2361.44 - lr: 0.000009 - momentum: 0.000000 |
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2023-10-17 15:29:16,244 epoch 8 - iter 432/1445 - loss 0.04312177 - time (sec): 21.46 - samples/sec: 2436.90 - lr: 0.000009 - momentum: 0.000000 |
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2023-10-17 15:29:23,284 epoch 8 - iter 576/1445 - loss 0.04654217 - time (sec): 28.50 - samples/sec: 2422.07 - lr: 0.000009 - momentum: 0.000000 |
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2023-10-17 15:29:30,118 epoch 8 - iter 720/1445 - loss 0.04836767 - time (sec): 35.34 - samples/sec: 2436.55 - lr: 0.000008 - momentum: 0.000000 |
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2023-10-17 15:29:37,165 epoch 8 - iter 864/1445 - loss 0.04435024 - time (sec): 42.38 - samples/sec: 2467.42 - lr: 0.000008 - momentum: 0.000000 |
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2023-10-17 15:29:44,054 epoch 8 - iter 1008/1445 - loss 0.04368948 - time (sec): 49.27 - samples/sec: 2483.93 - lr: 0.000008 - momentum: 0.000000 |
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2023-10-17 15:29:51,080 epoch 8 - iter 1152/1445 - loss 0.04126688 - time (sec): 56.30 - samples/sec: 2473.99 - lr: 0.000007 - momentum: 0.000000 |
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2023-10-17 15:29:58,174 epoch 8 - iter 1296/1445 - loss 0.03803387 - time (sec): 63.39 - samples/sec: 2489.99 - lr: 0.000007 - momentum: 0.000000 |
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2023-10-17 15:30:05,225 epoch 8 - iter 1440/1445 - loss 0.03611431 - time (sec): 70.44 - samples/sec: 2491.01 - lr: 0.000007 - momentum: 0.000000 |
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2023-10-17 15:30:05,479 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:30:05,479 EPOCH 8 done: loss 0.0360 - lr: 0.000007 |
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2023-10-17 15:30:08,822 DEV : loss 0.14063192903995514 - f1-score (micro avg) 0.8385 |
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2023-10-17 15:30:08,840 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:30:16,101 epoch 9 - iter 144/1445 - loss 0.00928856 - time (sec): 7.26 - samples/sec: 2645.70 - lr: 0.000006 - momentum: 0.000000 |
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2023-10-17 15:30:22,830 epoch 9 - iter 288/1445 - loss 0.01137305 - time (sec): 13.99 - samples/sec: 2509.03 - lr: 0.000006 - momentum: 0.000000 |
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2023-10-17 15:30:30,015 epoch 9 - iter 432/1445 - loss 0.01191848 - time (sec): 21.17 - samples/sec: 2557.99 - lr: 0.000006 - momentum: 0.000000 |
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2023-10-17 15:30:37,152 epoch 9 - iter 576/1445 - loss 0.01374329 - time (sec): 28.31 - samples/sec: 2558.62 - lr: 0.000005 - momentum: 0.000000 |
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2023-10-17 15:30:44,261 epoch 9 - iter 720/1445 - loss 0.01533254 - time (sec): 35.42 - samples/sec: 2528.74 - lr: 0.000005 - momentum: 0.000000 |
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2023-10-17 15:30:51,281 epoch 9 - iter 864/1445 - loss 0.01618231 - time (sec): 42.44 - samples/sec: 2487.04 - lr: 0.000005 - momentum: 0.000000 |
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2023-10-17 15:30:58,224 epoch 9 - iter 1008/1445 - loss 0.01852939 - time (sec): 49.38 - samples/sec: 2494.62 - lr: 0.000004 - momentum: 0.000000 |
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2023-10-17 15:31:05,713 epoch 9 - iter 1152/1445 - loss 0.02014171 - time (sec): 56.87 - samples/sec: 2484.98 - lr: 0.000004 - momentum: 0.000000 |
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2023-10-17 15:31:12,765 epoch 9 - iter 1296/1445 - loss 0.02108402 - time (sec): 63.92 - samples/sec: 2486.65 - lr: 0.000004 - momentum: 0.000000 |
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2023-10-17 15:31:19,478 epoch 9 - iter 1440/1445 - loss 0.02161319 - time (sec): 70.64 - samples/sec: 2483.77 - lr: 0.000003 - momentum: 0.000000 |
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2023-10-17 15:31:19,741 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:31:19,741 EPOCH 9 done: loss 0.0215 - lr: 0.000003 |
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2023-10-17 15:31:22,962 DEV : loss 0.15872889757156372 - f1-score (micro avg) 0.7959 |
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2023-10-17 15:31:22,980 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:31:29,837 epoch 10 - iter 144/1445 - loss 0.02704362 - time (sec): 6.86 - samples/sec: 2545.17 - lr: 0.000003 - momentum: 0.000000 |
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2023-10-17 15:31:36,571 epoch 10 - iter 288/1445 - loss 0.03061519 - time (sec): 13.59 - samples/sec: 2579.66 - lr: 0.000003 - momentum: 0.000000 |
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2023-10-17 15:31:43,536 epoch 10 - iter 432/1445 - loss 0.02831624 - time (sec): 20.55 - samples/sec: 2514.98 - lr: 0.000002 - momentum: 0.000000 |
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2023-10-17 15:31:50,270 epoch 10 - iter 576/1445 - loss 0.02567299 - time (sec): 27.29 - samples/sec: 2489.86 - lr: 0.000002 - momentum: 0.000000 |
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2023-10-17 15:31:57,397 epoch 10 - iter 720/1445 - loss 0.02269889 - time (sec): 34.42 - samples/sec: 2518.68 - lr: 0.000002 - momentum: 0.000000 |
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2023-10-17 15:32:04,472 epoch 10 - iter 864/1445 - loss 0.02217955 - time (sec): 41.49 - samples/sec: 2540.09 - lr: 0.000001 - momentum: 0.000000 |
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2023-10-17 15:32:11,337 epoch 10 - iter 1008/1445 - loss 0.02100455 - time (sec): 48.36 - samples/sec: 2523.83 - lr: 0.000001 - momentum: 0.000000 |
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2023-10-17 15:32:18,547 epoch 10 - iter 1152/1445 - loss 0.02030918 - time (sec): 55.57 - samples/sec: 2521.36 - lr: 0.000001 - momentum: 0.000000 |
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2023-10-17 15:32:25,459 epoch 10 - iter 1296/1445 - loss 0.01984945 - time (sec): 62.48 - samples/sec: 2530.72 - lr: 0.000000 - momentum: 0.000000 |
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2023-10-17 15:32:32,454 epoch 10 - iter 1440/1445 - loss 0.01908284 - time (sec): 69.47 - samples/sec: 2529.70 - lr: 0.000000 - momentum: 0.000000 |
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2023-10-17 15:32:32,675 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:32:32,675 EPOCH 10 done: loss 0.0191 - lr: 0.000000 |
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2023-10-17 15:32:35,914 DEV : loss 0.14746923744678497 - f1-score (micro avg) 0.8243 |
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2023-10-17 15:32:36,350 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 15:32:36,352 Loading model from best epoch ... |
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2023-10-17 15:32:38,127 SequenceTagger predicts: Dictionary with 13 tags: O, S-LOC, B-LOC, E-LOC, I-LOC, S-PER, B-PER, E-PER, I-PER, S-ORG, B-ORG, E-ORG, I-ORG |
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2023-10-17 15:32:40,946 |
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Results: |
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- F-score (micro) 0.8538 |
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- F-score (macro) 0.7349 |
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- Accuracy 0.7522 |
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By class: |
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precision recall f1-score support |
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PER 0.8758 0.8340 0.8544 482 |
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LOC 0.9385 0.8996 0.9186 458 |
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ORG 0.4286 0.4348 0.4317 69 |
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micro avg 0.8719 0.8365 0.8538 1009 |
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macro avg 0.7476 0.7228 0.7349 1009 |
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weighted avg 0.8737 0.8365 0.8546 1009 |
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2023-10-17 15:32:40,946 ---------------------------------------------------------------------------------------------------- |
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