| 2023-10-19 19:30:38,316 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:30:38,317 Model: "SequenceTagger( | |
| (embeddings): TransformerWordEmbeddings( | |
| (model): BertModel( | |
| (embeddings): BertEmbeddings( | |
| (word_embeddings): Embedding(32001, 128) | |
| (position_embeddings): Embedding(512, 128) | |
| (token_type_embeddings): Embedding(2, 128) | |
| (LayerNorm): LayerNorm((128,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (encoder): BertEncoder( | |
| (layer): ModuleList( | |
| (0-1): 2 x BertLayer( | |
| (attention): BertAttention( | |
| (self): BertSelfAttention( | |
| (query): Linear(in_features=128, out_features=128, bias=True) | |
| (key): Linear(in_features=128, out_features=128, bias=True) | |
| (value): Linear(in_features=128, out_features=128, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): BertSelfOutput( | |
| (dense): Linear(in_features=128, out_features=128, bias=True) | |
| (LayerNorm): LayerNorm((128,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): BertIntermediate( | |
| (dense): Linear(in_features=128, out_features=512, bias=True) | |
| (intermediate_act_fn): GELUActivation() | |
| ) | |
| (output): BertOutput( | |
| (dense): Linear(in_features=512, out_features=128, bias=True) | |
| (LayerNorm): LayerNorm((128,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| ) | |
| ) | |
| (pooler): BertPooler( | |
| (dense): Linear(in_features=128, out_features=128, bias=True) | |
| (activation): Tanh() | |
| ) | |
| ) | |
| ) | |
| (locked_dropout): LockedDropout(p=0.5) | |
| (linear): Linear(in_features=128, out_features=17, bias=True) | |
| (loss_function): CrossEntropyLoss() | |
| )" | |
| 2023-10-19 19:30:38,317 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:30:38,317 MultiCorpus: 7142 train + 698 dev + 2570 test sentences | |
| - NER_HIPE_2022 Corpus: 7142 train + 698 dev + 2570 test sentences - /root/.flair/datasets/ner_hipe_2022/v2.1/newseye/fr/with_doc_seperator | |
| 2023-10-19 19:30:38,317 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:30:38,317 Train: 7142 sentences | |
| 2023-10-19 19:30:38,317 (train_with_dev=False, train_with_test=False) | |
| 2023-10-19 19:30:38,317 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:30:38,317 Training Params: | |
| 2023-10-19 19:30:38,317 - learning_rate: "3e-05" | |
| 2023-10-19 19:30:38,317 - mini_batch_size: "4" | |
| 2023-10-19 19:30:38,317 - max_epochs: "10" | |
| 2023-10-19 19:30:38,317 - shuffle: "True" | |
| 2023-10-19 19:30:38,317 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:30:38,317 Plugins: | |
| 2023-10-19 19:30:38,317 - TensorboardLogger | |
| 2023-10-19 19:30:38,317 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-19 19:30:38,317 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:30:38,317 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-19 19:30:38,318 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-19 19:30:38,318 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:30:38,318 Computation: | |
| 2023-10-19 19:30:38,318 - compute on device: cuda:0 | |
| 2023-10-19 19:30:38,318 - embedding storage: none | |
| 2023-10-19 19:30:38,318 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:30:38,318 Model training base path: "hmbench-newseye/fr-dbmdz/bert-tiny-historic-multilingual-cased-bs4-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-1" | |
| 2023-10-19 19:30:38,318 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:30:38,318 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:30:38,318 Logging anything other than scalars to TensorBoard is currently not supported. | |
| 2023-10-19 19:30:42,345 epoch 1 - iter 178/1786 - loss 3.35557409 - time (sec): 4.03 - samples/sec: 6649.09 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-19 19:30:45,409 epoch 1 - iter 356/1786 - loss 3.04732355 - time (sec): 7.09 - samples/sec: 7258.29 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-19 19:30:48,452 epoch 1 - iter 534/1786 - loss 2.57347013 - time (sec): 10.13 - samples/sec: 7605.61 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-19 19:30:51,432 epoch 1 - iter 712/1786 - loss 2.19279281 - time (sec): 13.11 - samples/sec: 7628.30 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-19 19:30:54,374 epoch 1 - iter 890/1786 - loss 1.90940254 - time (sec): 16.06 - samples/sec: 7780.05 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-19 19:30:57,033 epoch 1 - iter 1068/1786 - loss 1.71174595 - time (sec): 18.72 - samples/sec: 7981.47 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-19 19:31:00,019 epoch 1 - iter 1246/1786 - loss 1.56052404 - time (sec): 21.70 - samples/sec: 8029.71 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-19 19:31:03,200 epoch 1 - iter 1424/1786 - loss 1.44384272 - time (sec): 24.88 - samples/sec: 8064.88 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-19 19:31:06,277 epoch 1 - iter 1602/1786 - loss 1.34797295 - time (sec): 27.96 - samples/sec: 8097.63 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-19 19:31:09,206 epoch 1 - iter 1780/1786 - loss 1.27247036 - time (sec): 30.89 - samples/sec: 8036.65 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-19 19:31:09,314 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:31:09,314 EPOCH 1 done: loss 1.2713 - lr: 0.000030 | |
| 2023-10-19 19:31:10,267 DEV : loss 0.3359092175960541 - f1-score (micro avg) 0.0487 | |
| 2023-10-19 19:31:10,280 saving best model | |
| 2023-10-19 19:31:10,314 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:31:13,387 epoch 2 - iter 178/1786 - loss 0.52150669 - time (sec): 3.07 - samples/sec: 7935.63 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-19 19:31:16,544 epoch 2 - iter 356/1786 - loss 0.47540073 - time (sec): 6.23 - samples/sec: 8020.47 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-19 19:31:19,413 epoch 2 - iter 534/1786 - loss 0.48292965 - time (sec): 9.10 - samples/sec: 8281.08 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-19 19:31:22,411 epoch 2 - iter 712/1786 - loss 0.47086550 - time (sec): 12.10 - samples/sec: 8348.10 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-19 19:31:25,366 epoch 2 - iter 890/1786 - loss 0.46122234 - time (sec): 15.05 - samples/sec: 8197.09 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-19 19:31:28,406 epoch 2 - iter 1068/1786 - loss 0.45031419 - time (sec): 18.09 - samples/sec: 8215.56 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-19 19:31:31,454 epoch 2 - iter 1246/1786 - loss 0.44704061 - time (sec): 21.14 - samples/sec: 8208.17 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-19 19:31:34,397 epoch 2 - iter 1424/1786 - loss 0.44759542 - time (sec): 24.08 - samples/sec: 8290.58 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-19 19:31:37,326 epoch 2 - iter 1602/1786 - loss 0.44190235 - time (sec): 27.01 - samples/sec: 8273.98 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-19 19:31:40,332 epoch 2 - iter 1780/1786 - loss 0.43665530 - time (sec): 30.02 - samples/sec: 8263.97 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-19 19:31:40,430 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:31:40,430 EPOCH 2 done: loss 0.4367 - lr: 0.000027 | |
| 2023-10-19 19:31:43,156 DEV : loss 0.2586509883403778 - f1-score (micro avg) 0.3582 | |
| 2023-10-19 19:31:43,169 saving best model | |
| 2023-10-19 19:31:43,203 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:31:46,369 epoch 3 - iter 178/1786 - loss 0.34074405 - time (sec): 3.17 - samples/sec: 7437.29 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-19 19:31:49,481 epoch 3 - iter 356/1786 - loss 0.35722086 - time (sec): 6.28 - samples/sec: 7581.36 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-19 19:31:52,534 epoch 3 - iter 534/1786 - loss 0.37202217 - time (sec): 9.33 - samples/sec: 7701.47 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-19 19:31:55,593 epoch 3 - iter 712/1786 - loss 0.36390494 - time (sec): 12.39 - samples/sec: 7782.00 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-19 19:31:58,617 epoch 3 - iter 890/1786 - loss 0.36309047 - time (sec): 15.41 - samples/sec: 7832.20 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-19 19:32:01,736 epoch 3 - iter 1068/1786 - loss 0.36131319 - time (sec): 18.53 - samples/sec: 7945.23 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-19 19:32:04,829 epoch 3 - iter 1246/1786 - loss 0.35798402 - time (sec): 21.63 - samples/sec: 7915.12 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-19 19:32:08,007 epoch 3 - iter 1424/1786 - loss 0.35852174 - time (sec): 24.80 - samples/sec: 7935.10 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-19 19:32:11,177 epoch 3 - iter 1602/1786 - loss 0.35173269 - time (sec): 27.97 - samples/sec: 7988.43 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-19 19:32:14,249 epoch 3 - iter 1780/1786 - loss 0.35039743 - time (sec): 31.05 - samples/sec: 7985.94 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-19 19:32:14,352 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:32:14,352 EPOCH 3 done: loss 0.3509 - lr: 0.000023 | |
| 2023-10-19 19:32:16,681 DEV : loss 0.23497113585472107 - f1-score (micro avg) 0.4239 | |
| 2023-10-19 19:32:16,695 saving best model | |
| 2023-10-19 19:32:16,729 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:32:19,764 epoch 4 - iter 178/1786 - loss 0.34808840 - time (sec): 3.03 - samples/sec: 7736.54 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-19 19:32:22,828 epoch 4 - iter 356/1786 - loss 0.33182945 - time (sec): 6.10 - samples/sec: 7914.57 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-19 19:32:25,874 epoch 4 - iter 534/1786 - loss 0.33144903 - time (sec): 9.14 - samples/sec: 8138.52 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-19 19:32:28,884 epoch 4 - iter 712/1786 - loss 0.32920436 - time (sec): 12.15 - samples/sec: 7962.87 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-19 19:32:31,833 epoch 4 - iter 890/1786 - loss 0.32373319 - time (sec): 15.10 - samples/sec: 8014.61 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-19 19:32:34,962 epoch 4 - iter 1068/1786 - loss 0.32588127 - time (sec): 18.23 - samples/sec: 8015.75 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-19 19:32:38,443 epoch 4 - iter 1246/1786 - loss 0.31956784 - time (sec): 21.71 - samples/sec: 7917.14 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-19 19:32:41,353 epoch 4 - iter 1424/1786 - loss 0.31923266 - time (sec): 24.62 - samples/sec: 8006.99 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-19 19:32:44,409 epoch 4 - iter 1602/1786 - loss 0.31502249 - time (sec): 27.68 - samples/sec: 8044.83 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-19 19:32:47,532 epoch 4 - iter 1780/1786 - loss 0.31282089 - time (sec): 30.80 - samples/sec: 8055.24 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-19 19:32:47,633 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:32:47,633 EPOCH 4 done: loss 0.3130 - lr: 0.000020 | |
| 2023-10-19 19:32:50,010 DEV : loss 0.2149001508951187 - f1-score (micro avg) 0.4653 | |
| 2023-10-19 19:32:50,023 saving best model | |
| 2023-10-19 19:32:50,057 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:32:53,143 epoch 5 - iter 178/1786 - loss 0.28225441 - time (sec): 3.08 - samples/sec: 8251.32 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-19 19:32:56,016 epoch 5 - iter 356/1786 - loss 0.29819281 - time (sec): 5.96 - samples/sec: 8472.79 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-19 19:32:59,080 epoch 5 - iter 534/1786 - loss 0.29855410 - time (sec): 9.02 - samples/sec: 8471.64 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-19 19:33:02,083 epoch 5 - iter 712/1786 - loss 0.30330707 - time (sec): 12.02 - samples/sec: 8205.57 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-19 19:33:05,219 epoch 5 - iter 890/1786 - loss 0.29989577 - time (sec): 15.16 - samples/sec: 8154.64 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-19 19:33:08,319 epoch 5 - iter 1068/1786 - loss 0.29542870 - time (sec): 18.26 - samples/sec: 8139.95 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-19 19:33:11,416 epoch 5 - iter 1246/1786 - loss 0.29344410 - time (sec): 21.36 - samples/sec: 8120.50 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-19 19:33:14,522 epoch 5 - iter 1424/1786 - loss 0.28918196 - time (sec): 24.46 - samples/sec: 8166.42 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-19 19:33:17,613 epoch 5 - iter 1602/1786 - loss 0.28833349 - time (sec): 27.55 - samples/sec: 8144.18 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-19 19:33:20,676 epoch 5 - iter 1780/1786 - loss 0.28461780 - time (sec): 30.62 - samples/sec: 8107.88 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-19 19:33:20,760 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:33:20,761 EPOCH 5 done: loss 0.2851 - lr: 0.000017 | |
| 2023-10-19 19:33:23,133 DEV : loss 0.2108898162841797 - f1-score (micro avg) 0.4851 | |
| 2023-10-19 19:33:23,146 saving best model | |
| 2023-10-19 19:33:23,180 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:33:26,371 epoch 6 - iter 178/1786 - loss 0.27194464 - time (sec): 3.19 - samples/sec: 7732.08 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-19 19:33:29,509 epoch 6 - iter 356/1786 - loss 0.25982245 - time (sec): 6.33 - samples/sec: 7990.52 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-19 19:33:32,616 epoch 6 - iter 534/1786 - loss 0.26314407 - time (sec): 9.44 - samples/sec: 8062.31 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-19 19:33:35,942 epoch 6 - iter 712/1786 - loss 0.26630751 - time (sec): 12.76 - samples/sec: 7878.24 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-19 19:33:38,609 epoch 6 - iter 890/1786 - loss 0.26812327 - time (sec): 15.43 - samples/sec: 8199.69 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-19 19:33:41,286 epoch 6 - iter 1068/1786 - loss 0.26573731 - time (sec): 18.11 - samples/sec: 8330.67 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-19 19:33:44,460 epoch 6 - iter 1246/1786 - loss 0.26870941 - time (sec): 21.28 - samples/sec: 8187.53 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-19 19:33:47,666 epoch 6 - iter 1424/1786 - loss 0.26843570 - time (sec): 24.49 - samples/sec: 8116.00 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-19 19:33:50,752 epoch 6 - iter 1602/1786 - loss 0.26563717 - time (sec): 27.57 - samples/sec: 8095.59 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-19 19:33:53,883 epoch 6 - iter 1780/1786 - loss 0.26643678 - time (sec): 30.70 - samples/sec: 8085.37 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-19 19:33:53,976 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:33:53,977 EPOCH 6 done: loss 0.2667 - lr: 0.000013 | |
| 2023-10-19 19:33:56,338 DEV : loss 0.20400717854499817 - f1-score (micro avg) 0.5092 | |
| 2023-10-19 19:33:56,353 saving best model | |
| 2023-10-19 19:33:56,384 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:33:58,908 epoch 7 - iter 178/1786 - loss 0.25727723 - time (sec): 2.52 - samples/sec: 9164.43 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-19 19:34:01,967 epoch 7 - iter 356/1786 - loss 0.26036317 - time (sec): 5.58 - samples/sec: 8619.91 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-19 19:34:05,035 epoch 7 - iter 534/1786 - loss 0.24886818 - time (sec): 8.65 - samples/sec: 8487.13 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-19 19:34:08,134 epoch 7 - iter 712/1786 - loss 0.25428910 - time (sec): 11.75 - samples/sec: 8325.67 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-19 19:34:11,331 epoch 7 - iter 890/1786 - loss 0.25487606 - time (sec): 14.95 - samples/sec: 8237.75 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-19 19:34:14,669 epoch 7 - iter 1068/1786 - loss 0.25037409 - time (sec): 18.28 - samples/sec: 8144.31 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-19 19:34:17,733 epoch 7 - iter 1246/1786 - loss 0.25246122 - time (sec): 21.35 - samples/sec: 8148.88 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-19 19:34:20,831 epoch 7 - iter 1424/1786 - loss 0.25394057 - time (sec): 24.45 - samples/sec: 8096.66 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-19 19:34:23,879 epoch 7 - iter 1602/1786 - loss 0.25424882 - time (sec): 27.49 - samples/sec: 8090.76 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-19 19:34:26,967 epoch 7 - iter 1780/1786 - loss 0.25556992 - time (sec): 30.58 - samples/sec: 8114.01 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-19 19:34:27,071 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:34:27,071 EPOCH 7 done: loss 0.2550 - lr: 0.000010 | |
| 2023-10-19 19:34:29,411 DEV : loss 0.19975362718105316 - f1-score (micro avg) 0.5137 | |
| 2023-10-19 19:34:29,425 saving best model | |
| 2023-10-19 19:34:29,460 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:34:32,551 epoch 8 - iter 178/1786 - loss 0.25894893 - time (sec): 3.09 - samples/sec: 8193.08 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-19 19:34:35,544 epoch 8 - iter 356/1786 - loss 0.25720911 - time (sec): 6.08 - samples/sec: 8254.42 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-19 19:34:38,679 epoch 8 - iter 534/1786 - loss 0.25536811 - time (sec): 9.22 - samples/sec: 7975.80 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-19 19:34:42,147 epoch 8 - iter 712/1786 - loss 0.24758044 - time (sec): 12.69 - samples/sec: 7802.40 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-19 19:34:45,184 epoch 8 - iter 890/1786 - loss 0.24736965 - time (sec): 15.72 - samples/sec: 7829.00 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-19 19:34:48,231 epoch 8 - iter 1068/1786 - loss 0.24333603 - time (sec): 18.77 - samples/sec: 8003.01 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-19 19:34:51,246 epoch 8 - iter 1246/1786 - loss 0.24489911 - time (sec): 21.78 - samples/sec: 7953.46 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-19 19:34:54,308 epoch 8 - iter 1424/1786 - loss 0.24241203 - time (sec): 24.85 - samples/sec: 7988.83 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-19 19:34:57,453 epoch 8 - iter 1602/1786 - loss 0.24403072 - time (sec): 27.99 - samples/sec: 8015.58 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-19 19:35:00,570 epoch 8 - iter 1780/1786 - loss 0.24583775 - time (sec): 31.11 - samples/sec: 7963.02 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-19 19:35:00,674 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:35:00,674 EPOCH 8 done: loss 0.2452 - lr: 0.000007 | |
| 2023-10-19 19:35:03,077 DEV : loss 0.19914978742599487 - f1-score (micro avg) 0.5189 | |
| 2023-10-19 19:35:03,090 saving best model | |
| 2023-10-19 19:35:03,123 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:35:06,163 epoch 9 - iter 178/1786 - loss 0.23821530 - time (sec): 3.04 - samples/sec: 8011.02 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-19 19:35:09,155 epoch 9 - iter 356/1786 - loss 0.25309649 - time (sec): 6.03 - samples/sec: 8089.52 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-19 19:35:12,272 epoch 9 - iter 534/1786 - loss 0.24190772 - time (sec): 9.15 - samples/sec: 7958.63 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-19 19:35:15,346 epoch 9 - iter 712/1786 - loss 0.24222367 - time (sec): 12.22 - samples/sec: 8057.06 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-19 19:35:18,365 epoch 9 - iter 890/1786 - loss 0.24155227 - time (sec): 15.24 - samples/sec: 8034.84 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-19 19:35:21,347 epoch 9 - iter 1068/1786 - loss 0.24208353 - time (sec): 18.22 - samples/sec: 8156.84 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-19 19:35:24,351 epoch 9 - iter 1246/1786 - loss 0.24108614 - time (sec): 21.23 - samples/sec: 8109.56 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-19 19:35:27,403 epoch 9 - iter 1424/1786 - loss 0.24019162 - time (sec): 24.28 - samples/sec: 8156.05 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-19 19:35:30,466 epoch 9 - iter 1602/1786 - loss 0.24303458 - time (sec): 27.34 - samples/sec: 8144.81 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-19 19:35:33,616 epoch 9 - iter 1780/1786 - loss 0.23944010 - time (sec): 30.49 - samples/sec: 8129.33 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-19 19:35:33,716 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:35:33,716 EPOCH 9 done: loss 0.2392 - lr: 0.000003 | |
| 2023-10-19 19:35:36,496 DEV : loss 0.19566838443279266 - f1-score (micro avg) 0.5251 | |
| 2023-10-19 19:35:36,509 saving best model | |
| 2023-10-19 19:35:36,543 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:35:39,683 epoch 10 - iter 178/1786 - loss 0.25183541 - time (sec): 3.14 - samples/sec: 7949.52 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-19 19:35:42,858 epoch 10 - iter 356/1786 - loss 0.24654755 - time (sec): 6.31 - samples/sec: 7969.63 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-19 19:35:45,912 epoch 10 - iter 534/1786 - loss 0.24620089 - time (sec): 9.37 - samples/sec: 8111.22 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-19 19:35:48,917 epoch 10 - iter 712/1786 - loss 0.23937163 - time (sec): 12.37 - samples/sec: 8029.79 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-19 19:35:52,075 epoch 10 - iter 890/1786 - loss 0.24211773 - time (sec): 15.53 - samples/sec: 7931.61 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-19 19:35:55,143 epoch 10 - iter 1068/1786 - loss 0.24202751 - time (sec): 18.60 - samples/sec: 7953.73 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-19 19:35:58,209 epoch 10 - iter 1246/1786 - loss 0.24174603 - time (sec): 21.67 - samples/sec: 7979.86 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-19 19:36:01,244 epoch 10 - iter 1424/1786 - loss 0.23782131 - time (sec): 24.70 - samples/sec: 8023.65 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-19 19:36:04,337 epoch 10 - iter 1602/1786 - loss 0.23640511 - time (sec): 27.79 - samples/sec: 7996.89 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-19 19:36:07,434 epoch 10 - iter 1780/1786 - loss 0.23538347 - time (sec): 30.89 - samples/sec: 8035.23 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-19 19:36:07,525 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:36:07,525 EPOCH 10 done: loss 0.2355 - lr: 0.000000 | |
| 2023-10-19 19:36:09,907 DEV : loss 0.19619056582450867 - f1-score (micro avg) 0.5165 | |
| 2023-10-19 19:36:09,947 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-19 19:36:09,947 Loading model from best epoch ... | |
| 2023-10-19 19:36:10,025 SequenceTagger predicts: Dictionary with 17 tags: O, S-PER, B-PER, E-PER, I-PER, S-LOC, B-LOC, E-LOC, I-LOC, S-ORG, B-ORG, E-ORG, I-ORG, S-HumanProd, B-HumanProd, E-HumanProd, I-HumanProd | |
| 2023-10-19 19:36:14,436 | |
| Results: | |
| - F-score (micro) 0.4104 | |
| - F-score (macro) 0.2422 | |
| - Accuracy 0.2681 | |
| By class: | |
| precision recall f1-score support | |
| LOC 0.4062 0.5297 0.4598 1095 | |
| PER 0.4160 0.4822 0.4467 1012 | |
| ORG 0.0895 0.0476 0.0622 357 | |
| HumanProd 0.0000 0.0000 0.0000 33 | |
| micro avg 0.3887 0.4345 0.4104 2497 | |
| macro avg 0.2279 0.2649 0.2422 2497 | |
| weighted avg 0.3595 0.4345 0.3915 2497 | |
| 2023-10-19 19:36:14,436 ---------------------------------------------------------------------------------------------------- | |