| 2023-10-17 11:10:35,946 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:10:35,947 Model: "SequenceTagger( | |
| (embeddings): TransformerWordEmbeddings( | |
| (model): ElectraModel( | |
| (embeddings): ElectraEmbeddings( | |
| (word_embeddings): Embedding(32001, 768) | |
| (position_embeddings): Embedding(512, 768) | |
| (token_type_embeddings): Embedding(2, 768) | |
| (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (encoder): ElectraEncoder( | |
| (layer): ModuleList( | |
| (0-11): 12 x ElectraLayer( | |
| (attention): ElectraAttention( | |
| (self): ElectraSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): ElectraSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): ElectraIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| (intermediate_act_fn): GELUActivation() | |
| ) | |
| (output): ElectraOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| ) | |
| ) | |
| ) | |
| ) | |
| (locked_dropout): LockedDropout(p=0.5) | |
| (linear): Linear(in_features=768, out_features=13, bias=True) | |
| (loss_function): CrossEntropyLoss() | |
| )" | |
| 2023-10-17 11:10:35,947 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:10:35,947 MultiCorpus: 7936 train + 992 dev + 992 test sentences | |
| - NER_ICDAR_EUROPEANA Corpus: 7936 train + 992 dev + 992 test sentences - /root/.flair/datasets/ner_icdar_europeana/fr | |
| 2023-10-17 11:10:35,947 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:10:35,947 Train: 7936 sentences | |
| 2023-10-17 11:10:35,947 (train_with_dev=False, train_with_test=False) | |
| 2023-10-17 11:10:35,947 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:10:35,947 Training Params: | |
| 2023-10-17 11:10:35,947 - learning_rate: "3e-05" | |
| 2023-10-17 11:10:35,947 - mini_batch_size: "8" | |
| 2023-10-17 11:10:35,947 - max_epochs: "10" | |
| 2023-10-17 11:10:35,947 - shuffle: "True" | |
| 2023-10-17 11:10:35,947 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:10:35,947 Plugins: | |
| 2023-10-17 11:10:35,947 - TensorboardLogger | |
| 2023-10-17 11:10:35,947 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-17 11:10:35,947 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:10:35,947 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-17 11:10:35,948 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-17 11:10:35,948 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:10:35,948 Computation: | |
| 2023-10-17 11:10:35,948 - compute on device: cuda:0 | |
| 2023-10-17 11:10:35,948 - embedding storage: none | |
| 2023-10-17 11:10:35,948 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:10:35,948 Model training base path: "hmbench-icdar/fr-hmteams/teams-base-historic-multilingual-discriminator-bs8-wsFalse-e10-lr3e-05-poolingfirst-layers-1-crfFalse-1" | |
| 2023-10-17 11:10:35,948 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:10:35,948 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:10:35,948 Logging anything other than scalars to TensorBoard is currently not supported. | |
| 2023-10-17 11:10:41,616 epoch 1 - iter 99/992 - loss 2.35539114 - time (sec): 5.67 - samples/sec: 2855.26 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 11:10:47,538 epoch 1 - iter 198/992 - loss 1.40680709 - time (sec): 11.59 - samples/sec: 2868.20 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 11:10:53,608 epoch 1 - iter 297/992 - loss 1.04115910 - time (sec): 17.66 - samples/sec: 2809.86 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 11:10:59,239 epoch 1 - iter 396/992 - loss 0.84719360 - time (sec): 23.29 - samples/sec: 2807.76 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 11:11:05,055 epoch 1 - iter 495/992 - loss 0.71535594 - time (sec): 29.11 - samples/sec: 2811.66 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 11:11:11,034 epoch 1 - iter 594/992 - loss 0.62145829 - time (sec): 35.08 - samples/sec: 2811.70 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 11:11:16,796 epoch 1 - iter 693/992 - loss 0.55480225 - time (sec): 40.85 - samples/sec: 2810.35 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 11:11:22,867 epoch 1 - iter 792/992 - loss 0.50361870 - time (sec): 46.92 - samples/sec: 2798.42 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 11:11:28,860 epoch 1 - iter 891/992 - loss 0.46410739 - time (sec): 52.91 - samples/sec: 2782.88 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 11:11:34,919 epoch 1 - iter 990/992 - loss 0.43212790 - time (sec): 58.97 - samples/sec: 2775.25 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-17 11:11:35,041 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:11:35,041 EPOCH 1 done: loss 0.4316 - lr: 0.000030 | |
| 2023-10-17 11:11:38,162 DEV : loss 0.08676033467054367 - f1-score (micro avg) 0.7199 | |
| 2023-10-17 11:11:38,183 saving best model | |
| 2023-10-17 11:11:38,587 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:11:44,550 epoch 2 - iter 99/992 - loss 0.11696385 - time (sec): 5.96 - samples/sec: 2835.52 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-17 11:11:50,416 epoch 2 - iter 198/992 - loss 0.11618124 - time (sec): 11.83 - samples/sec: 2800.02 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 11:11:56,471 epoch 2 - iter 297/992 - loss 0.11331183 - time (sec): 17.88 - samples/sec: 2774.95 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 11:12:02,513 epoch 2 - iter 396/992 - loss 0.11261654 - time (sec): 23.92 - samples/sec: 2777.28 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-17 11:12:08,304 epoch 2 - iter 495/992 - loss 0.11070004 - time (sec): 29.72 - samples/sec: 2778.60 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 11:12:14,490 epoch 2 - iter 594/992 - loss 0.10711394 - time (sec): 35.90 - samples/sec: 2767.06 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 11:12:20,440 epoch 2 - iter 693/992 - loss 0.10655133 - time (sec): 41.85 - samples/sec: 2770.96 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-17 11:12:26,149 epoch 2 - iter 792/992 - loss 0.10605544 - time (sec): 47.56 - samples/sec: 2768.67 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 11:12:31,669 epoch 2 - iter 891/992 - loss 0.10492989 - time (sec): 53.08 - samples/sec: 2774.40 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 11:12:37,575 epoch 2 - iter 990/992 - loss 0.10483049 - time (sec): 58.99 - samples/sec: 2774.39 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-17 11:12:37,684 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:12:37,684 EPOCH 2 done: loss 0.1047 - lr: 0.000027 | |
| 2023-10-17 11:12:41,045 DEV : loss 0.08092305064201355 - f1-score (micro avg) 0.7476 | |
| 2023-10-17 11:12:41,065 saving best model | |
| 2023-10-17 11:12:41,541 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:12:47,547 epoch 3 - iter 99/992 - loss 0.07406015 - time (sec): 6.00 - samples/sec: 2761.66 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 11:12:53,879 epoch 3 - iter 198/992 - loss 0.07571237 - time (sec): 12.33 - samples/sec: 2664.69 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 11:12:59,712 epoch 3 - iter 297/992 - loss 0.07767047 - time (sec): 18.17 - samples/sec: 2730.93 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-17 11:13:05,609 epoch 3 - iter 396/992 - loss 0.07451733 - time (sec): 24.06 - samples/sec: 2760.33 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 11:13:11,373 epoch 3 - iter 495/992 - loss 0.07393624 - time (sec): 29.83 - samples/sec: 2772.86 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 11:13:17,373 epoch 3 - iter 594/992 - loss 0.07426966 - time (sec): 35.83 - samples/sec: 2748.48 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-17 11:13:23,257 epoch 3 - iter 693/992 - loss 0.07362660 - time (sec): 41.71 - samples/sec: 2752.24 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 11:13:29,199 epoch 3 - iter 792/992 - loss 0.07377128 - time (sec): 47.65 - samples/sec: 2752.64 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 11:13:35,203 epoch 3 - iter 891/992 - loss 0.07333761 - time (sec): 53.66 - samples/sec: 2756.36 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-17 11:13:41,096 epoch 3 - iter 990/992 - loss 0.07353970 - time (sec): 59.55 - samples/sec: 2747.42 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 11:13:41,223 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:13:41,223 EPOCH 3 done: loss 0.0738 - lr: 0.000023 | |
| 2023-10-17 11:13:44,598 DEV : loss 0.09785806387662888 - f1-score (micro avg) 0.7773 | |
| 2023-10-17 11:13:44,619 saving best model | |
| 2023-10-17 11:13:45,115 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:13:50,991 epoch 4 - iter 99/992 - loss 0.04715289 - time (sec): 5.87 - samples/sec: 2795.06 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 11:13:57,306 epoch 4 - iter 198/992 - loss 0.04859458 - time (sec): 12.19 - samples/sec: 2801.69 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-17 11:14:03,532 epoch 4 - iter 297/992 - loss 0.05296561 - time (sec): 18.41 - samples/sec: 2765.99 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 11:14:09,520 epoch 4 - iter 396/992 - loss 0.05345139 - time (sec): 24.40 - samples/sec: 2763.54 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 11:14:15,297 epoch 4 - iter 495/992 - loss 0.05257484 - time (sec): 30.18 - samples/sec: 2773.12 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-17 11:14:21,014 epoch 4 - iter 594/992 - loss 0.05331551 - time (sec): 35.90 - samples/sec: 2766.59 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 11:14:26,711 epoch 4 - iter 693/992 - loss 0.05207488 - time (sec): 41.59 - samples/sec: 2763.02 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 11:14:32,689 epoch 4 - iter 792/992 - loss 0.05223178 - time (sec): 47.57 - samples/sec: 2754.12 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-17 11:14:38,645 epoch 4 - iter 891/992 - loss 0.05295532 - time (sec): 53.53 - samples/sec: 2759.52 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 11:14:44,333 epoch 4 - iter 990/992 - loss 0.05240036 - time (sec): 59.22 - samples/sec: 2765.51 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 11:14:44,449 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:14:44,450 EPOCH 4 done: loss 0.0524 - lr: 0.000020 | |
| 2023-10-17 11:14:47,878 DEV : loss 0.13641133904457092 - f1-score (micro avg) 0.7649 | |
| 2023-10-17 11:14:47,900 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:14:53,676 epoch 5 - iter 99/992 - loss 0.04378565 - time (sec): 5.77 - samples/sec: 2815.74 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-17 11:14:59,857 epoch 5 - iter 198/992 - loss 0.04178287 - time (sec): 11.96 - samples/sec: 2802.61 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 11:15:05,790 epoch 5 - iter 297/992 - loss 0.04075583 - time (sec): 17.89 - samples/sec: 2806.75 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 11:15:12,022 epoch 5 - iter 396/992 - loss 0.04344692 - time (sec): 24.12 - samples/sec: 2807.67 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-17 11:15:18,006 epoch 5 - iter 495/992 - loss 0.04136461 - time (sec): 30.10 - samples/sec: 2795.08 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 11:15:23,779 epoch 5 - iter 594/992 - loss 0.04108893 - time (sec): 35.88 - samples/sec: 2786.92 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 11:15:29,897 epoch 5 - iter 693/992 - loss 0.04186090 - time (sec): 42.00 - samples/sec: 2771.48 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-17 11:15:35,744 epoch 5 - iter 792/992 - loss 0.04169627 - time (sec): 47.84 - samples/sec: 2763.70 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 11:15:41,665 epoch 5 - iter 891/992 - loss 0.04129249 - time (sec): 53.76 - samples/sec: 2756.65 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 11:15:47,396 epoch 5 - iter 990/992 - loss 0.04068447 - time (sec): 59.49 - samples/sec: 2750.32 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-17 11:15:47,517 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:15:47,517 EPOCH 5 done: loss 0.0406 - lr: 0.000017 | |
| 2023-10-17 11:15:50,892 DEV : loss 0.16494178771972656 - f1-score (micro avg) 0.7729 | |
| 2023-10-17 11:15:50,912 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:15:57,006 epoch 6 - iter 99/992 - loss 0.03725393 - time (sec): 6.09 - samples/sec: 2699.56 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 11:16:02,998 epoch 6 - iter 198/992 - loss 0.03560557 - time (sec): 12.08 - samples/sec: 2702.68 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 11:16:09,230 epoch 6 - iter 297/992 - loss 0.03361870 - time (sec): 18.32 - samples/sec: 2743.42 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-17 11:16:15,197 epoch 6 - iter 396/992 - loss 0.03257403 - time (sec): 24.28 - samples/sec: 2744.09 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 11:16:21,178 epoch 6 - iter 495/992 - loss 0.03060213 - time (sec): 30.26 - samples/sec: 2755.79 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 11:16:27,122 epoch 6 - iter 594/992 - loss 0.03138720 - time (sec): 36.21 - samples/sec: 2753.62 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-17 11:16:32,894 epoch 6 - iter 693/992 - loss 0.03183636 - time (sec): 41.98 - samples/sec: 2747.03 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 11:16:38,722 epoch 6 - iter 792/992 - loss 0.03166393 - time (sec): 47.81 - samples/sec: 2743.57 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 11:16:44,633 epoch 6 - iter 891/992 - loss 0.03185778 - time (sec): 53.72 - samples/sec: 2742.04 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-17 11:16:50,574 epoch 6 - iter 990/992 - loss 0.03147109 - time (sec): 59.66 - samples/sec: 2741.74 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 11:16:50,693 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:16:50,693 EPOCH 6 done: loss 0.0314 - lr: 0.000013 | |
| 2023-10-17 11:16:54,493 DEV : loss 0.1783766746520996 - f1-score (micro avg) 0.7611 | |
| 2023-10-17 11:16:54,513 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:17:00,463 epoch 7 - iter 99/992 - loss 0.01479405 - time (sec): 5.95 - samples/sec: 2739.57 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 11:17:06,433 epoch 7 - iter 198/992 - loss 0.01855344 - time (sec): 11.92 - samples/sec: 2753.51 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-17 11:17:12,717 epoch 7 - iter 297/992 - loss 0.02129056 - time (sec): 18.20 - samples/sec: 2722.81 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 11:17:18,568 epoch 7 - iter 396/992 - loss 0.01977589 - time (sec): 24.05 - samples/sec: 2729.72 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 11:17:24,376 epoch 7 - iter 495/992 - loss 0.02105573 - time (sec): 29.86 - samples/sec: 2744.65 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-17 11:17:30,317 epoch 7 - iter 594/992 - loss 0.02074744 - time (sec): 35.80 - samples/sec: 2749.34 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 11:17:36,372 epoch 7 - iter 693/992 - loss 0.02168930 - time (sec): 41.86 - samples/sec: 2741.67 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 11:17:42,180 epoch 7 - iter 792/992 - loss 0.02173930 - time (sec): 47.67 - samples/sec: 2733.92 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-17 11:17:48,139 epoch 7 - iter 891/992 - loss 0.02294377 - time (sec): 53.62 - samples/sec: 2749.12 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 11:17:53,862 epoch 7 - iter 990/992 - loss 0.02347962 - time (sec): 59.35 - samples/sec: 2758.26 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 11:17:53,969 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:17:53,969 EPOCH 7 done: loss 0.0234 - lr: 0.000010 | |
| 2023-10-17 11:17:57,318 DEV : loss 0.19467273354530334 - f1-score (micro avg) 0.7607 | |
| 2023-10-17 11:17:57,339 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:18:03,287 epoch 8 - iter 99/992 - loss 0.01125503 - time (sec): 5.95 - samples/sec: 2752.98 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-17 11:18:09,176 epoch 8 - iter 198/992 - loss 0.01332788 - time (sec): 11.84 - samples/sec: 2737.34 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 11:18:15,530 epoch 8 - iter 297/992 - loss 0.01421025 - time (sec): 18.19 - samples/sec: 2750.10 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 11:18:21,448 epoch 8 - iter 396/992 - loss 0.01395360 - time (sec): 24.11 - samples/sec: 2741.71 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-17 11:18:27,369 epoch 8 - iter 495/992 - loss 0.01451229 - time (sec): 30.03 - samples/sec: 2770.54 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 11:18:33,364 epoch 8 - iter 594/992 - loss 0.01486056 - time (sec): 36.02 - samples/sec: 2773.53 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 11:18:39,063 epoch 8 - iter 693/992 - loss 0.01514888 - time (sec): 41.72 - samples/sec: 2770.78 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-17 11:18:44,658 epoch 8 - iter 792/992 - loss 0.01607490 - time (sec): 47.32 - samples/sec: 2760.01 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 11:18:50,490 epoch 8 - iter 891/992 - loss 0.01626578 - time (sec): 53.15 - samples/sec: 2769.74 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 11:18:56,558 epoch 8 - iter 990/992 - loss 0.01631606 - time (sec): 59.22 - samples/sec: 2763.32 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-17 11:18:56,694 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:18:56,694 EPOCH 8 done: loss 0.0163 - lr: 0.000007 | |
| 2023-10-17 11:19:00,034 DEV : loss 0.21547943353652954 - f1-score (micro avg) 0.768 | |
| 2023-10-17 11:19:00,054 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:19:05,751 epoch 9 - iter 99/992 - loss 0.01171116 - time (sec): 5.70 - samples/sec: 2781.21 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 11:19:11,906 epoch 9 - iter 198/992 - loss 0.01092092 - time (sec): 11.85 - samples/sec: 2802.05 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 11:19:18,125 epoch 9 - iter 297/992 - loss 0.01147235 - time (sec): 18.07 - samples/sec: 2790.05 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-17 11:19:24,182 epoch 9 - iter 396/992 - loss 0.01124791 - time (sec): 24.13 - samples/sec: 2763.88 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 11:19:29,873 epoch 9 - iter 495/992 - loss 0.01092981 - time (sec): 29.82 - samples/sec: 2768.94 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 11:19:35,804 epoch 9 - iter 594/992 - loss 0.01048007 - time (sec): 35.75 - samples/sec: 2761.59 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-17 11:19:41,603 epoch 9 - iter 693/992 - loss 0.01045002 - time (sec): 41.55 - samples/sec: 2762.43 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 11:19:47,572 epoch 9 - iter 792/992 - loss 0.01109786 - time (sec): 47.52 - samples/sec: 2768.35 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 11:19:53,411 epoch 9 - iter 891/992 - loss 0.01231061 - time (sec): 53.36 - samples/sec: 2768.52 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-17 11:19:59,359 epoch 9 - iter 990/992 - loss 0.01301436 - time (sec): 59.30 - samples/sec: 2760.13 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 11:19:59,476 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:19:59,477 EPOCH 9 done: loss 0.0130 - lr: 0.000003 | |
| 2023-10-17 11:20:02,832 DEV : loss 0.22187332808971405 - f1-score (micro avg) 0.7691 | |
| 2023-10-17 11:20:02,853 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:20:08,757 epoch 10 - iter 99/992 - loss 0.00856091 - time (sec): 5.90 - samples/sec: 2797.08 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 11:20:14,415 epoch 10 - iter 198/992 - loss 0.00758860 - time (sec): 11.56 - samples/sec: 2781.04 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-17 11:20:20,240 epoch 10 - iter 297/992 - loss 0.00994920 - time (sec): 17.39 - samples/sec: 2796.55 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 11:20:26,342 epoch 10 - iter 396/992 - loss 0.01046124 - time (sec): 23.49 - samples/sec: 2759.19 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 11:20:32,235 epoch 10 - iter 495/992 - loss 0.01035655 - time (sec): 29.38 - samples/sec: 2742.35 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-17 11:20:38,312 epoch 10 - iter 594/992 - loss 0.00989221 - time (sec): 35.46 - samples/sec: 2748.31 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 11:20:44,329 epoch 10 - iter 693/992 - loss 0.00978816 - time (sec): 41.47 - samples/sec: 2763.82 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 11:20:50,049 epoch 10 - iter 792/992 - loss 0.00975569 - time (sec): 47.19 - samples/sec: 2777.56 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-17 11:20:55,974 epoch 10 - iter 891/992 - loss 0.00989868 - time (sec): 53.12 - samples/sec: 2766.47 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-17 11:21:02,019 epoch 10 - iter 990/992 - loss 0.01026192 - time (sec): 59.16 - samples/sec: 2766.98 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-17 11:21:02,120 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:21:02,120 EPOCH 10 done: loss 0.0103 - lr: 0.000000 | |
| 2023-10-17 11:21:06,039 DEV : loss 0.2308199256658554 - f1-score (micro avg) 0.762 | |
| 2023-10-17 11:21:06,467 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-17 11:21:06,468 Loading model from best epoch ... | |
| 2023-10-17 11:21:07,858 SequenceTagger predicts: Dictionary with 13 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 | |
| 2023-10-17 11:21:11,195 | |
| Results: | |
| - F-score (micro) 0.7821 | |
| - F-score (macro) 0.6943 | |
| - Accuracy 0.6678 | |
| By class: | |
| precision recall f1-score support | |
| LOC 0.8291 0.8519 0.8404 655 | |
| PER 0.6887 0.7937 0.7375 223 | |
| ORG 0.6800 0.4016 0.5050 127 | |
| micro avg 0.7821 0.7821 0.7821 1005 | |
| macro avg 0.7326 0.6824 0.6943 1005 | |
| weighted avg 0.7791 0.7821 0.7752 1005 | |
| 2023-10-17 11:21:11,195 ---------------------------------------------------------------------------------------------------- | |