| 2023-10-14 00:15:26,580 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 00:15:26,582 Model: "SequenceTagger( | |
| (embeddings): ByT5Embeddings( | |
| (model): T5EncoderModel( | |
| (shared): Embedding(384, 1472) | |
| (encoder): T5Stack( | |
| (embed_tokens): Embedding(384, 1472) | |
| (block): ModuleList( | |
| (0): T5Block( | |
| (layer): ModuleList( | |
| (0): T5LayerSelfAttention( | |
| (SelfAttention): T5Attention( | |
| (q): Linear(in_features=1472, out_features=384, bias=False) | |
| (k): Linear(in_features=1472, out_features=384, bias=False) | |
| (v): Linear(in_features=1472, out_features=384, bias=False) | |
| (o): Linear(in_features=384, out_features=1472, bias=False) | |
| (relative_attention_bias): Embedding(32, 6) | |
| ) | |
| (layer_norm): FusedRMSNorm(torch.Size([1472]), eps=1e-06, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (1): T5LayerFF( | |
| (DenseReluDense): T5DenseGatedActDense( | |
| (wi_0): Linear(in_features=1472, out_features=3584, bias=False) | |
| (wi_1): Linear(in_features=1472, out_features=3584, bias=False) | |
| (wo): Linear(in_features=3584, out_features=1472, bias=False) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| (act): NewGELUActivation() | |
| ) | |
| (layer_norm): FusedRMSNorm(torch.Size([1472]), eps=1e-06, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| ) | |
| (1-11): 11 x T5Block( | |
| (layer): ModuleList( | |
| (0): T5LayerSelfAttention( | |
| (SelfAttention): T5Attention( | |
| (q): Linear(in_features=1472, out_features=384, bias=False) | |
| (k): Linear(in_features=1472, out_features=384, bias=False) | |
| (v): Linear(in_features=1472, out_features=384, bias=False) | |
| (o): Linear(in_features=384, out_features=1472, bias=False) | |
| ) | |
| (layer_norm): FusedRMSNorm(torch.Size([1472]), eps=1e-06, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (1): T5LayerFF( | |
| (DenseReluDense): T5DenseGatedActDense( | |
| (wi_0): Linear(in_features=1472, out_features=3584, bias=False) | |
| (wi_1): Linear(in_features=1472, out_features=3584, bias=False) | |
| (wo): Linear(in_features=3584, out_features=1472, bias=False) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| (act): NewGELUActivation() | |
| ) | |
| (layer_norm): FusedRMSNorm(torch.Size([1472]), eps=1e-06, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| ) | |
| ) | |
| (final_layer_norm): FusedRMSNorm(torch.Size([1472]), eps=1e-06, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| ) | |
| (locked_dropout): LockedDropout(p=0.5) | |
| (linear): Linear(in_features=1472, out_features=13, bias=True) | |
| (loss_function): CrossEntropyLoss() | |
| )" | |
| 2023-10-14 00:15:26,582 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 00:15:26,582 MultiCorpus: 14465 train + 1392 dev + 2432 test sentences | |
| - NER_HIPE_2022 Corpus: 14465 train + 1392 dev + 2432 test sentences - /root/.flair/datasets/ner_hipe_2022/v2.1/letemps/fr/with_doc_seperator | |
| 2023-10-14 00:15:26,583 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 00:15:26,583 Train: 14465 sentences | |
| 2023-10-14 00:15:26,583 (train_with_dev=False, train_with_test=False) | |
| 2023-10-14 00:15:26,583 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 00:15:26,583 Training Params: | |
| 2023-10-14 00:15:26,583 - learning_rate: "0.00016" | |
| 2023-10-14 00:15:26,583 - mini_batch_size: "8" | |
| 2023-10-14 00:15:26,583 - max_epochs: "10" | |
| 2023-10-14 00:15:26,583 - shuffle: "True" | |
| 2023-10-14 00:15:26,583 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 00:15:26,583 Plugins: | |
| 2023-10-14 00:15:26,583 - TensorboardLogger | |
| 2023-10-14 00:15:26,583 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-14 00:15:26,584 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 00:15:26,584 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-14 00:15:26,584 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-14 00:15:26,584 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 00:15:26,584 Computation: | |
| 2023-10-14 00:15:26,584 - compute on device: cuda:0 | |
| 2023-10-14 00:15:26,584 - embedding storage: none | |
| 2023-10-14 00:15:26,584 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 00:15:26,584 Model training base path: "hmbench-letemps/fr-hmbyt5-preliminary/byt5-small-historic-multilingual-span20-flax-bs8-wsFalse-e10-lr0.00016-poolingfirst-layers-1-crfFalse-3" | |
| 2023-10-14 00:15:26,584 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 00:15:26,584 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 00:15:26,584 Logging anything other than scalars to TensorBoard is currently not supported. | |
| 2023-10-14 00:16:57,553 epoch 1 - iter 180/1809 - loss 2.51944389 - time (sec): 90.97 - samples/sec: 413.65 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-14 00:18:29,092 epoch 1 - iter 360/1809 - loss 2.26637505 - time (sec): 182.51 - samples/sec: 406.16 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-14 00:20:01,815 epoch 1 - iter 540/1809 - loss 1.90816370 - time (sec): 275.23 - samples/sec: 409.55 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-14 00:21:31,625 epoch 1 - iter 720/1809 - loss 1.56194036 - time (sec): 365.04 - samples/sec: 413.28 - lr: 0.000064 - momentum: 0.000000 | |
| 2023-10-14 00:23:01,817 epoch 1 - iter 900/1809 - loss 1.30444465 - time (sec): 455.23 - samples/sec: 414.24 - lr: 0.000080 - momentum: 0.000000 | |
| 2023-10-14 00:24:33,627 epoch 1 - iter 1080/1809 - loss 1.11961360 - time (sec): 547.04 - samples/sec: 413.43 - lr: 0.000095 - momentum: 0.000000 | |
| 2023-10-14 00:26:03,228 epoch 1 - iter 1260/1809 - loss 0.98696147 - time (sec): 636.64 - samples/sec: 412.31 - lr: 0.000111 - momentum: 0.000000 | |
| 2023-10-14 00:27:35,596 epoch 1 - iter 1440/1809 - loss 0.88259280 - time (sec): 729.01 - samples/sec: 411.99 - lr: 0.000127 - momentum: 0.000000 | |
| 2023-10-14 00:29:08,136 epoch 1 - iter 1620/1809 - loss 0.79457894 - time (sec): 821.55 - samples/sec: 413.43 - lr: 0.000143 - momentum: 0.000000 | |
| 2023-10-14 00:30:36,487 epoch 1 - iter 1800/1809 - loss 0.72720679 - time (sec): 909.90 - samples/sec: 415.88 - lr: 0.000159 - momentum: 0.000000 | |
| 2023-10-14 00:30:40,375 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 00:30:40,375 EPOCH 1 done: loss 0.7248 - lr: 0.000159 | |
| 2023-10-14 00:31:18,366 DEV : loss 0.13587747514247894 - f1-score (micro avg) 0.5512 | |
| 2023-10-14 00:31:18,430 saving best model | |
| 2023-10-14 00:31:19,337 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 00:32:49,760 epoch 2 - iter 180/1809 - loss 0.10182046 - time (sec): 90.42 - samples/sec: 417.47 - lr: 0.000158 - momentum: 0.000000 | |
| 2023-10-14 00:34:19,933 epoch 2 - iter 360/1809 - loss 0.10191876 - time (sec): 180.59 - samples/sec: 413.42 - lr: 0.000156 - momentum: 0.000000 | |
| 2023-10-14 00:35:49,015 epoch 2 - iter 540/1809 - loss 0.09941428 - time (sec): 269.68 - samples/sec: 429.78 - lr: 0.000155 - momentum: 0.000000 | |
| 2023-10-14 00:37:16,788 epoch 2 - iter 720/1809 - loss 0.09701065 - time (sec): 357.45 - samples/sec: 432.34 - lr: 0.000153 - momentum: 0.000000 | |
| 2023-10-14 00:38:45,501 epoch 2 - iter 900/1809 - loss 0.09626668 - time (sec): 446.16 - samples/sec: 431.73 - lr: 0.000151 - momentum: 0.000000 | |
| 2023-10-14 00:40:13,863 epoch 2 - iter 1080/1809 - loss 0.09449862 - time (sec): 534.52 - samples/sec: 428.08 - lr: 0.000149 - momentum: 0.000000 | |
| 2023-10-14 00:41:41,920 epoch 2 - iter 1260/1809 - loss 0.09221887 - time (sec): 622.58 - samples/sec: 427.87 - lr: 0.000148 - momentum: 0.000000 | |
| 2023-10-14 00:43:10,709 epoch 2 - iter 1440/1809 - loss 0.09076303 - time (sec): 711.37 - samples/sec: 426.55 - lr: 0.000146 - momentum: 0.000000 | |
| 2023-10-14 00:44:41,103 epoch 2 - iter 1620/1809 - loss 0.08931886 - time (sec): 801.76 - samples/sec: 425.61 - lr: 0.000144 - momentum: 0.000000 | |
| 2023-10-14 00:46:10,438 epoch 2 - iter 1800/1809 - loss 0.08787461 - time (sec): 891.10 - samples/sec: 424.53 - lr: 0.000142 - momentum: 0.000000 | |
| 2023-10-14 00:46:14,383 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 00:46:14,383 EPOCH 2 done: loss 0.0879 - lr: 0.000142 | |
| 2023-10-14 00:46:52,480 DEV : loss 0.10200479626655579 - f1-score (micro avg) 0.6091 | |
| 2023-10-14 00:46:52,536 saving best model | |
| 2023-10-14 00:46:55,099 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 00:48:24,885 epoch 3 - iter 180/1809 - loss 0.06314980 - time (sec): 89.78 - samples/sec: 416.42 - lr: 0.000140 - momentum: 0.000000 | |
| 2023-10-14 00:49:56,919 epoch 3 - iter 360/1809 - loss 0.05882268 - time (sec): 181.82 - samples/sec: 422.98 - lr: 0.000139 - momentum: 0.000000 | |
| 2023-10-14 00:51:27,745 epoch 3 - iter 540/1809 - loss 0.05798093 - time (sec): 272.64 - samples/sec: 420.56 - lr: 0.000137 - momentum: 0.000000 | |
| 2023-10-14 00:52:57,778 epoch 3 - iter 720/1809 - loss 0.05728226 - time (sec): 362.67 - samples/sec: 419.92 - lr: 0.000135 - momentum: 0.000000 | |
| 2023-10-14 00:54:27,582 epoch 3 - iter 900/1809 - loss 0.05773776 - time (sec): 452.48 - samples/sec: 423.51 - lr: 0.000133 - momentum: 0.000000 | |
| 2023-10-14 00:55:56,659 epoch 3 - iter 1080/1809 - loss 0.05718530 - time (sec): 541.56 - samples/sec: 424.38 - lr: 0.000132 - momentum: 0.000000 | |
| 2023-10-14 00:57:26,791 epoch 3 - iter 1260/1809 - loss 0.05787219 - time (sec): 631.69 - samples/sec: 420.89 - lr: 0.000130 - momentum: 0.000000 | |
| 2023-10-14 00:58:55,840 epoch 3 - iter 1440/1809 - loss 0.05720897 - time (sec): 720.74 - samples/sec: 420.23 - lr: 0.000128 - momentum: 0.000000 | |
| 2023-10-14 01:00:24,566 epoch 3 - iter 1620/1809 - loss 0.05641677 - time (sec): 809.46 - samples/sec: 419.21 - lr: 0.000126 - momentum: 0.000000 | |
| 2023-10-14 01:01:57,412 epoch 3 - iter 1800/1809 - loss 0.05640597 - time (sec): 902.31 - samples/sec: 418.82 - lr: 0.000125 - momentum: 0.000000 | |
| 2023-10-14 01:02:01,841 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 01:02:01,842 EPOCH 3 done: loss 0.0563 - lr: 0.000125 | |
| 2023-10-14 01:02:41,767 DEV : loss 0.13950783014297485 - f1-score (micro avg) 0.6198 | |
| 2023-10-14 01:02:41,831 saving best model | |
| 2023-10-14 01:02:44,406 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 01:04:14,083 epoch 4 - iter 180/1809 - loss 0.04170364 - time (sec): 89.67 - samples/sec: 407.77 - lr: 0.000123 - momentum: 0.000000 | |
| 2023-10-14 01:05:46,581 epoch 4 - iter 360/1809 - loss 0.03858075 - time (sec): 182.17 - samples/sec: 411.86 - lr: 0.000121 - momentum: 0.000000 | |
| 2023-10-14 01:07:17,093 epoch 4 - iter 540/1809 - loss 0.03981754 - time (sec): 272.68 - samples/sec: 412.97 - lr: 0.000119 - momentum: 0.000000 | |
| 2023-10-14 01:08:47,525 epoch 4 - iter 720/1809 - loss 0.03847050 - time (sec): 363.11 - samples/sec: 411.25 - lr: 0.000117 - momentum: 0.000000 | |
| 2023-10-14 01:10:18,340 epoch 4 - iter 900/1809 - loss 0.03892181 - time (sec): 453.93 - samples/sec: 411.93 - lr: 0.000116 - momentum: 0.000000 | |
| 2023-10-14 01:11:50,274 epoch 4 - iter 1080/1809 - loss 0.04023787 - time (sec): 545.86 - samples/sec: 415.14 - lr: 0.000114 - momentum: 0.000000 | |
| 2023-10-14 01:13:22,824 epoch 4 - iter 1260/1809 - loss 0.04131278 - time (sec): 638.41 - samples/sec: 415.03 - lr: 0.000112 - momentum: 0.000000 | |
| 2023-10-14 01:14:51,158 epoch 4 - iter 1440/1809 - loss 0.04134067 - time (sec): 726.75 - samples/sec: 416.20 - lr: 0.000110 - momentum: 0.000000 | |
| 2023-10-14 01:16:20,419 epoch 4 - iter 1620/1809 - loss 0.04065918 - time (sec): 816.01 - samples/sec: 418.02 - lr: 0.000109 - momentum: 0.000000 | |
| 2023-10-14 01:17:50,525 epoch 4 - iter 1800/1809 - loss 0.04036183 - time (sec): 906.11 - samples/sec: 417.55 - lr: 0.000107 - momentum: 0.000000 | |
| 2023-10-14 01:17:54,624 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 01:17:54,624 EPOCH 4 done: loss 0.0403 - lr: 0.000107 | |
| 2023-10-14 01:18:35,366 DEV : loss 0.19245745241641998 - f1-score (micro avg) 0.6321 | |
| 2023-10-14 01:18:35,431 saving best model | |
| 2023-10-14 01:18:38,017 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 01:20:09,743 epoch 5 - iter 180/1809 - loss 0.02576443 - time (sec): 91.72 - samples/sec: 418.78 - lr: 0.000105 - momentum: 0.000000 | |
| 2023-10-14 01:21:44,400 epoch 5 - iter 360/1809 - loss 0.02641732 - time (sec): 186.38 - samples/sec: 408.40 - lr: 0.000103 - momentum: 0.000000 | |
| 2023-10-14 01:23:15,834 epoch 5 - iter 540/1809 - loss 0.02651451 - time (sec): 277.81 - samples/sec: 407.70 - lr: 0.000101 - momentum: 0.000000 | |
| 2023-10-14 01:24:43,605 epoch 5 - iter 720/1809 - loss 0.02751988 - time (sec): 365.58 - samples/sec: 409.65 - lr: 0.000100 - momentum: 0.000000 | |
| 2023-10-14 01:26:12,328 epoch 5 - iter 900/1809 - loss 0.02767393 - time (sec): 454.31 - samples/sec: 414.53 - lr: 0.000098 - momentum: 0.000000 | |
| 2023-10-14 01:27:41,085 epoch 5 - iter 1080/1809 - loss 0.02796036 - time (sec): 543.06 - samples/sec: 416.11 - lr: 0.000096 - momentum: 0.000000 | |
| 2023-10-14 01:29:10,393 epoch 5 - iter 1260/1809 - loss 0.02785250 - time (sec): 632.37 - samples/sec: 414.60 - lr: 0.000094 - momentum: 0.000000 | |
| 2023-10-14 01:30:45,505 epoch 5 - iter 1440/1809 - loss 0.02843191 - time (sec): 727.48 - samples/sec: 412.25 - lr: 0.000093 - momentum: 0.000000 | |
| 2023-10-14 01:32:18,477 epoch 5 - iter 1620/1809 - loss 0.02924215 - time (sec): 820.46 - samples/sec: 412.99 - lr: 0.000091 - momentum: 0.000000 | |
| 2023-10-14 01:33:51,099 epoch 5 - iter 1800/1809 - loss 0.02925813 - time (sec): 913.08 - samples/sec: 414.13 - lr: 0.000089 - momentum: 0.000000 | |
| 2023-10-14 01:33:55,154 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 01:33:55,155 EPOCH 5 done: loss 0.0293 - lr: 0.000089 | |
| 2023-10-14 01:34:33,142 DEV : loss 0.2196071296930313 - f1-score (micro avg) 0.6454 | |
| 2023-10-14 01:34:33,199 saving best model | |
| 2023-10-14 01:34:35,762 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 01:36:06,097 epoch 6 - iter 180/1809 - loss 0.01696868 - time (sec): 90.33 - samples/sec: 434.02 - lr: 0.000087 - momentum: 0.000000 | |
| 2023-10-14 01:37:36,160 epoch 6 - iter 360/1809 - loss 0.01685237 - time (sec): 180.39 - samples/sec: 426.33 - lr: 0.000085 - momentum: 0.000000 | |
| 2023-10-14 01:39:05,475 epoch 6 - iter 540/1809 - loss 0.02067304 - time (sec): 269.71 - samples/sec: 422.42 - lr: 0.000084 - momentum: 0.000000 | |
| 2023-10-14 01:40:35,631 epoch 6 - iter 720/1809 - loss 0.02166279 - time (sec): 359.87 - samples/sec: 418.94 - lr: 0.000082 - momentum: 0.000000 | |
| 2023-10-14 01:42:08,370 epoch 6 - iter 900/1809 - loss 0.02213544 - time (sec): 452.60 - samples/sec: 412.98 - lr: 0.000080 - momentum: 0.000000 | |
| 2023-10-14 01:43:40,493 epoch 6 - iter 1080/1809 - loss 0.02224410 - time (sec): 544.73 - samples/sec: 412.51 - lr: 0.000078 - momentum: 0.000000 | |
| 2023-10-14 01:45:13,554 epoch 6 - iter 1260/1809 - loss 0.02163785 - time (sec): 637.79 - samples/sec: 414.18 - lr: 0.000077 - momentum: 0.000000 | |
| 2023-10-14 01:46:46,037 epoch 6 - iter 1440/1809 - loss 0.02152121 - time (sec): 730.27 - samples/sec: 415.13 - lr: 0.000075 - momentum: 0.000000 | |
| 2023-10-14 01:48:18,422 epoch 6 - iter 1620/1809 - loss 0.02245358 - time (sec): 822.66 - samples/sec: 412.61 - lr: 0.000073 - momentum: 0.000000 | |
| 2023-10-14 01:49:50,889 epoch 6 - iter 1800/1809 - loss 0.02230601 - time (sec): 915.12 - samples/sec: 413.40 - lr: 0.000071 - momentum: 0.000000 | |
| 2023-10-14 01:49:54,955 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 01:49:54,956 EPOCH 6 done: loss 0.0222 - lr: 0.000071 | |
| 2023-10-14 01:50:36,500 DEV : loss 0.25768402218818665 - f1-score (micro avg) 0.6629 | |
| 2023-10-14 01:50:36,559 saving best model | |
| 2023-10-14 01:50:39,137 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 01:52:12,077 epoch 7 - iter 180/1809 - loss 0.00921054 - time (sec): 92.94 - samples/sec: 411.47 - lr: 0.000069 - momentum: 0.000000 | |
| 2023-10-14 01:53:50,733 epoch 7 - iter 360/1809 - loss 0.01168701 - time (sec): 191.59 - samples/sec: 395.89 - lr: 0.000068 - momentum: 0.000000 | |
| 2023-10-14 01:55:21,611 epoch 7 - iter 540/1809 - loss 0.01305153 - time (sec): 282.47 - samples/sec: 400.63 - lr: 0.000066 - momentum: 0.000000 | |
| 2023-10-14 01:56:55,925 epoch 7 - iter 720/1809 - loss 0.01260349 - time (sec): 376.78 - samples/sec: 404.80 - lr: 0.000064 - momentum: 0.000000 | |
| 2023-10-14 01:58:26,714 epoch 7 - iter 900/1809 - loss 0.01297523 - time (sec): 467.57 - samples/sec: 406.34 - lr: 0.000062 - momentum: 0.000000 | |
| 2023-10-14 02:00:02,490 epoch 7 - iter 1080/1809 - loss 0.01344991 - time (sec): 563.35 - samples/sec: 404.29 - lr: 0.000061 - momentum: 0.000000 | |
| 2023-10-14 02:01:34,331 epoch 7 - iter 1260/1809 - loss 0.01433938 - time (sec): 655.19 - samples/sec: 406.81 - lr: 0.000059 - momentum: 0.000000 | |
| 2023-10-14 02:03:06,795 epoch 7 - iter 1440/1809 - loss 0.01477713 - time (sec): 747.65 - samples/sec: 406.47 - lr: 0.000057 - momentum: 0.000000 | |
| 2023-10-14 02:04:40,603 epoch 7 - iter 1620/1809 - loss 0.01477570 - time (sec): 841.46 - samples/sec: 406.11 - lr: 0.000055 - momentum: 0.000000 | |
| 2023-10-14 02:06:15,178 epoch 7 - iter 1800/1809 - loss 0.01511790 - time (sec): 936.04 - samples/sec: 404.12 - lr: 0.000053 - momentum: 0.000000 | |
| 2023-10-14 02:06:19,433 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 02:06:19,433 EPOCH 7 done: loss 0.0151 - lr: 0.000053 | |
| 2023-10-14 02:06:59,410 DEV : loss 0.2951534390449524 - f1-score (micro avg) 0.6663 | |
| 2023-10-14 02:06:59,467 saving best model | |
| 2023-10-14 02:07:02,034 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 02:08:31,365 epoch 8 - iter 180/1809 - loss 0.00690787 - time (sec): 89.33 - samples/sec: 414.43 - lr: 0.000052 - momentum: 0.000000 | |
| 2023-10-14 02:10:01,793 epoch 8 - iter 360/1809 - loss 0.01015270 - time (sec): 179.75 - samples/sec: 417.93 - lr: 0.000050 - momentum: 0.000000 | |
| 2023-10-14 02:11:31,245 epoch 8 - iter 540/1809 - loss 0.01075555 - time (sec): 269.21 - samples/sec: 425.42 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-14 02:12:59,192 epoch 8 - iter 720/1809 - loss 0.01026295 - time (sec): 357.15 - samples/sec: 426.20 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-14 02:14:29,940 epoch 8 - iter 900/1809 - loss 0.00994762 - time (sec): 447.90 - samples/sec: 425.93 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-14 02:16:04,150 epoch 8 - iter 1080/1809 - loss 0.00979174 - time (sec): 542.11 - samples/sec: 420.45 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-14 02:17:34,169 epoch 8 - iter 1260/1809 - loss 0.01043605 - time (sec): 632.13 - samples/sec: 420.83 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-14 02:19:02,279 epoch 8 - iter 1440/1809 - loss 0.01048305 - time (sec): 720.24 - samples/sec: 420.80 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-14 02:20:31,156 epoch 8 - iter 1620/1809 - loss 0.01031134 - time (sec): 809.12 - samples/sec: 421.20 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-14 02:21:59,294 epoch 8 - iter 1800/1809 - loss 0.01018123 - time (sec): 897.26 - samples/sec: 421.63 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-14 02:22:03,202 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 02:22:03,202 EPOCH 8 done: loss 0.0102 - lr: 0.000036 | |
| 2023-10-14 02:22:42,340 DEV : loss 0.31866809725761414 - f1-score (micro avg) 0.6638 | |
| 2023-10-14 02:22:42,399 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 02:24:15,293 epoch 9 - iter 180/1809 - loss 0.00817136 - time (sec): 92.89 - samples/sec: 415.41 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-14 02:25:48,900 epoch 9 - iter 360/1809 - loss 0.00980844 - time (sec): 186.50 - samples/sec: 417.93 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-14 02:27:21,286 epoch 9 - iter 540/1809 - loss 0.00968269 - time (sec): 278.88 - samples/sec: 413.52 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-14 02:28:53,866 epoch 9 - iter 720/1809 - loss 0.00851234 - time (sec): 371.46 - samples/sec: 413.77 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-14 02:30:25,601 epoch 9 - iter 900/1809 - loss 0.00876138 - time (sec): 463.20 - samples/sec: 412.00 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-14 02:31:58,342 epoch 9 - iter 1080/1809 - loss 0.00835601 - time (sec): 555.94 - samples/sec: 411.87 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-14 02:33:29,812 epoch 9 - iter 1260/1809 - loss 0.00813399 - time (sec): 647.41 - samples/sec: 411.93 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-14 02:35:00,772 epoch 9 - iter 1440/1809 - loss 0.00791238 - time (sec): 738.37 - samples/sec: 411.24 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-14 02:36:32,257 epoch 9 - iter 1620/1809 - loss 0.00783074 - time (sec): 829.86 - samples/sec: 409.66 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-14 02:38:03,837 epoch 9 - iter 1800/1809 - loss 0.00756760 - time (sec): 921.44 - samples/sec: 410.66 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-14 02:38:07,713 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 02:38:07,713 EPOCH 9 done: loss 0.0076 - lr: 0.000018 | |
| 2023-10-14 02:38:45,463 DEV : loss 0.3397609293460846 - f1-score (micro avg) 0.6699 | |
| 2023-10-14 02:38:45,524 saving best model | |
| 2023-10-14 02:38:48,090 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 02:40:17,848 epoch 10 - iter 180/1809 - loss 0.00675340 - time (sec): 89.75 - samples/sec: 418.97 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-14 02:41:47,430 epoch 10 - iter 360/1809 - loss 0.00699592 - time (sec): 179.34 - samples/sec: 410.52 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-14 02:43:19,155 epoch 10 - iter 540/1809 - loss 0.00674174 - time (sec): 271.06 - samples/sec: 414.12 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-14 02:44:53,881 epoch 10 - iter 720/1809 - loss 0.00580321 - time (sec): 365.79 - samples/sec: 407.45 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-14 02:46:33,110 epoch 10 - iter 900/1809 - loss 0.00563464 - time (sec): 465.02 - samples/sec: 403.22 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-14 02:48:05,921 epoch 10 - iter 1080/1809 - loss 0.00536878 - time (sec): 557.83 - samples/sec: 403.01 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-14 02:49:38,498 epoch 10 - iter 1260/1809 - loss 0.00519036 - time (sec): 650.40 - samples/sec: 406.07 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-14 02:51:10,923 epoch 10 - iter 1440/1809 - loss 0.00506535 - time (sec): 742.83 - samples/sec: 405.69 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-14 02:52:43,275 epoch 10 - iter 1620/1809 - loss 0.00520096 - time (sec): 835.18 - samples/sec: 407.55 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-14 02:54:18,302 epoch 10 - iter 1800/1809 - loss 0.00505952 - time (sec): 930.21 - samples/sec: 406.29 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-14 02:54:22,857 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 02:54:22,857 EPOCH 10 done: loss 0.0050 - lr: 0.000000 | |
| 2023-10-14 02:55:02,618 DEV : loss 0.34813550114631653 - f1-score (micro avg) 0.6654 | |
| 2023-10-14 02:55:03,588 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 02:55:03,590 Loading model from best epoch ... | |
| 2023-10-14 02:55:07,452 SequenceTagger predicts: Dictionary with 13 tags: O, S-loc, B-loc, E-loc, I-loc, S-pers, B-pers, E-pers, I-pers, S-org, B-org, E-org, I-org | |
| 2023-10-14 02:56:07,325 | |
| Results: | |
| - F-score (micro) 0.6407 | |
| - F-score (macro) 0.4712 | |
| - Accuracy 0.4813 | |
| By class: | |
| precision recall f1-score support | |
| loc 0.6545 0.7563 0.7017 591 | |
| pers 0.5705 0.7143 0.6343 357 | |
| org 0.1000 0.0633 0.0775 79 | |
| micro avg 0.5992 0.6884 0.6407 1027 | |
| macro avg 0.4416 0.5113 0.4712 1027 | |
| weighted avg 0.5826 0.6884 0.6303 1027 | |
| 2023-10-14 02:56:07,325 ---------------------------------------------------------------------------------------------------- | |