| 2023-10-18 21:25:18,822 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:25:18,823 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=13, bias=True) | |
| (loss_function): CrossEntropyLoss() | |
| )" | |
| 2023-10-18 21:25:18,823 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:25:18,823 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 | |
| 2023-10-18 21:25:18,823 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:25:18,823 Train: 7936 sentences | |
| 2023-10-18 21:25:18,823 (train_with_dev=False, train_with_test=False) | |
| 2023-10-18 21:25:18,823 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:25:18,823 Training Params: | |
| 2023-10-18 21:25:18,823 - learning_rate: "5e-05" | |
| 2023-10-18 21:25:18,823 - mini_batch_size: "4" | |
| 2023-10-18 21:25:18,823 - max_epochs: "10" | |
| 2023-10-18 21:25:18,823 - shuffle: "True" | |
| 2023-10-18 21:25:18,823 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:25:18,823 Plugins: | |
| 2023-10-18 21:25:18,823 - TensorboardLogger | |
| 2023-10-18 21:25:18,823 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-18 21:25:18,823 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:25:18,823 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-18 21:25:18,823 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-18 21:25:18,823 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:25:18,823 Computation: | |
| 2023-10-18 21:25:18,824 - compute on device: cuda:0 | |
| 2023-10-18 21:25:18,824 - embedding storage: none | |
| 2023-10-18 21:25:18,824 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:25:18,824 Model training base path: "hmbench-icdar/fr-dbmdz/bert-tiny-historic-multilingual-cased-bs4-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-4" | |
| 2023-10-18 21:25:18,824 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:25:18,824 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:25:18,824 Logging anything other than scalars to TensorBoard is currently not supported. | |
| 2023-10-18 21:25:21,871 epoch 1 - iter 198/1984 - loss 3.05001127 - time (sec): 3.05 - samples/sec: 5386.70 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-18 21:25:24,628 epoch 1 - iter 396/1984 - loss 2.47724953 - time (sec): 5.80 - samples/sec: 5922.14 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-18 21:25:27,667 epoch 1 - iter 594/1984 - loss 1.93619435 - time (sec): 8.84 - samples/sec: 5709.43 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-18 21:25:30,706 epoch 1 - iter 792/1984 - loss 1.58401951 - time (sec): 11.88 - samples/sec: 5618.92 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-18 21:25:33,758 epoch 1 - iter 990/1984 - loss 1.35401175 - time (sec): 14.93 - samples/sec: 5563.79 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-18 21:25:36,794 epoch 1 - iter 1188/1984 - loss 1.20410373 - time (sec): 17.97 - samples/sec: 5524.66 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-18 21:25:39,832 epoch 1 - iter 1386/1984 - loss 1.09303606 - time (sec): 21.01 - samples/sec: 5470.81 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-18 21:25:42,910 epoch 1 - iter 1584/1984 - loss 0.99807468 - time (sec): 24.09 - samples/sec: 5451.75 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-18 21:25:45,923 epoch 1 - iter 1782/1984 - loss 0.92290600 - time (sec): 27.10 - samples/sec: 5442.29 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-18 21:25:49,008 epoch 1 - iter 1980/1984 - loss 0.86043295 - time (sec): 30.18 - samples/sec: 5425.81 - lr: 0.000050 - momentum: 0.000000 | |
| 2023-10-18 21:25:49,068 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:25:49,068 EPOCH 1 done: loss 0.8594 - lr: 0.000050 | |
| 2023-10-18 21:25:50,560 DEV : loss 0.21192067861557007 - f1-score (micro avg) 0.2945 | |
| 2023-10-18 21:25:50,578 saving best model | |
| 2023-10-18 21:25:50,613 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:25:53,727 epoch 2 - iter 198/1984 - loss 0.30950366 - time (sec): 3.11 - samples/sec: 4927.98 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-18 21:25:56,796 epoch 2 - iter 396/1984 - loss 0.28151013 - time (sec): 6.18 - samples/sec: 5145.74 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-18 21:25:59,865 epoch 2 - iter 594/1984 - loss 0.28431083 - time (sec): 9.25 - samples/sec: 5342.97 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-18 21:26:02,940 epoch 2 - iter 792/1984 - loss 0.27867074 - time (sec): 12.33 - samples/sec: 5398.12 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-18 21:26:06,023 epoch 2 - iter 990/1984 - loss 0.27356192 - time (sec): 15.41 - samples/sec: 5362.82 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-18 21:26:09,040 epoch 2 - iter 1188/1984 - loss 0.26808423 - time (sec): 18.43 - samples/sec: 5380.47 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-18 21:26:11,822 epoch 2 - iter 1386/1984 - loss 0.26113663 - time (sec): 21.21 - samples/sec: 5451.69 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-18 21:26:14,900 epoch 2 - iter 1584/1984 - loss 0.25788671 - time (sec): 24.29 - samples/sec: 5438.15 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-18 21:26:17,947 epoch 2 - iter 1782/1984 - loss 0.25525919 - time (sec): 27.33 - samples/sec: 5421.86 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-18 21:26:20,762 epoch 2 - iter 1980/1984 - loss 0.25444187 - time (sec): 30.15 - samples/sec: 5429.33 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-18 21:26:20,822 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:26:20,822 EPOCH 2 done: loss 0.2546 - lr: 0.000044 | |
| 2023-10-18 21:26:22,634 DEV : loss 0.16650356352329254 - f1-score (micro avg) 0.4051 | |
| 2023-10-18 21:26:22,654 saving best model | |
| 2023-10-18 21:26:22,690 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:26:25,787 epoch 3 - iter 198/1984 - loss 0.21161120 - time (sec): 3.10 - samples/sec: 5483.96 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-18 21:26:28,837 epoch 3 - iter 396/1984 - loss 0.20257772 - time (sec): 6.15 - samples/sec: 5328.22 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-18 21:26:31,767 epoch 3 - iter 594/1984 - loss 0.21363359 - time (sec): 9.08 - samples/sec: 5582.96 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-18 21:26:34,842 epoch 3 - iter 792/1984 - loss 0.20789207 - time (sec): 12.15 - samples/sec: 5470.71 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-18 21:26:37,879 epoch 3 - iter 990/1984 - loss 0.21055604 - time (sec): 15.19 - samples/sec: 5444.07 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-18 21:26:40,954 epoch 3 - iter 1188/1984 - loss 0.20723027 - time (sec): 18.26 - samples/sec: 5444.07 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-18 21:26:44,031 epoch 3 - iter 1386/1984 - loss 0.20657276 - time (sec): 21.34 - samples/sec: 5424.20 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-18 21:26:47,055 epoch 3 - iter 1584/1984 - loss 0.20547288 - time (sec): 24.36 - samples/sec: 5434.88 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-18 21:26:50,070 epoch 3 - iter 1782/1984 - loss 0.20632094 - time (sec): 27.38 - samples/sec: 5413.63 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-18 21:26:53,106 epoch 3 - iter 1980/1984 - loss 0.20495296 - time (sec): 30.41 - samples/sec: 5376.32 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-18 21:26:53,176 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:26:53,176 EPOCH 3 done: loss 0.2046 - lr: 0.000039 | |
| 2023-10-18 21:26:55,394 DEV : loss 0.15022146701812744 - f1-score (micro avg) 0.5321 | |
| 2023-10-18 21:26:55,413 saving best model | |
| 2023-10-18 21:26:55,447 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:26:58,566 epoch 4 - iter 198/1984 - loss 0.18075544 - time (sec): 3.12 - samples/sec: 5291.79 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-18 21:27:01,634 epoch 4 - iter 396/1984 - loss 0.18240152 - time (sec): 6.19 - samples/sec: 5143.93 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-18 21:27:04,650 epoch 4 - iter 594/1984 - loss 0.17441944 - time (sec): 9.20 - samples/sec: 5216.19 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-18 21:27:07,674 epoch 4 - iter 792/1984 - loss 0.17622746 - time (sec): 12.23 - samples/sec: 5214.64 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-18 21:27:10,762 epoch 4 - iter 990/1984 - loss 0.17870370 - time (sec): 15.31 - samples/sec: 5266.42 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-18 21:27:13,782 epoch 4 - iter 1188/1984 - loss 0.17730408 - time (sec): 18.33 - samples/sec: 5322.13 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-18 21:27:16,890 epoch 4 - iter 1386/1984 - loss 0.17390393 - time (sec): 21.44 - samples/sec: 5403.97 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-18 21:27:20,088 epoch 4 - iter 1584/1984 - loss 0.17431675 - time (sec): 24.64 - samples/sec: 5366.83 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-18 21:27:23,148 epoch 4 - iter 1782/1984 - loss 0.17801776 - time (sec): 27.70 - samples/sec: 5333.04 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-18 21:27:26,231 epoch 4 - iter 1980/1984 - loss 0.17957717 - time (sec): 30.78 - samples/sec: 5317.52 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-18 21:27:26,291 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:27:26,291 EPOCH 4 done: loss 0.1797 - lr: 0.000033 | |
| 2023-10-18 21:27:28,115 DEV : loss 0.14466138184070587 - f1-score (micro avg) 0.5683 | |
| 2023-10-18 21:27:28,133 saving best model | |
| 2023-10-18 21:27:28,167 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:27:31,281 epoch 5 - iter 198/1984 - loss 0.18093443 - time (sec): 3.11 - samples/sec: 5540.53 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-18 21:27:34,301 epoch 5 - iter 396/1984 - loss 0.17976008 - time (sec): 6.13 - samples/sec: 5491.12 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-18 21:27:37,345 epoch 5 - iter 594/1984 - loss 0.17027389 - time (sec): 9.18 - samples/sec: 5444.29 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-18 21:27:40,347 epoch 5 - iter 792/1984 - loss 0.16509799 - time (sec): 12.18 - samples/sec: 5422.24 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-18 21:27:43,351 epoch 5 - iter 990/1984 - loss 0.16344421 - time (sec): 15.18 - samples/sec: 5364.28 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-18 21:27:46,391 epoch 5 - iter 1188/1984 - loss 0.16463321 - time (sec): 18.22 - samples/sec: 5341.67 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-18 21:27:49,456 epoch 5 - iter 1386/1984 - loss 0.16486788 - time (sec): 21.29 - samples/sec: 5405.39 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-18 21:27:52,493 epoch 5 - iter 1584/1984 - loss 0.16396812 - time (sec): 24.33 - samples/sec: 5388.54 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-18 21:27:55,556 epoch 5 - iter 1782/1984 - loss 0.16439615 - time (sec): 27.39 - samples/sec: 5372.41 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-18 21:27:58,492 epoch 5 - iter 1980/1984 - loss 0.16305676 - time (sec): 30.32 - samples/sec: 5399.14 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-18 21:27:58,549 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:27:58,549 EPOCH 5 done: loss 0.1629 - lr: 0.000028 | |
| 2023-10-18 21:28:00,391 DEV : loss 0.1396612972021103 - f1-score (micro avg) 0.6016 | |
| 2023-10-18 21:28:00,410 saving best model | |
| 2023-10-18 21:28:00,443 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:28:03,439 epoch 6 - iter 198/1984 - loss 0.16107360 - time (sec): 3.00 - samples/sec: 5139.73 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-18 21:28:06,549 epoch 6 - iter 396/1984 - loss 0.15421664 - time (sec): 6.11 - samples/sec: 5364.46 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-18 21:28:09,674 epoch 6 - iter 594/1984 - loss 0.15915795 - time (sec): 9.23 - samples/sec: 5330.25 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-18 21:28:12,713 epoch 6 - iter 792/1984 - loss 0.15438849 - time (sec): 12.27 - samples/sec: 5364.46 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-18 21:28:15,664 epoch 6 - iter 990/1984 - loss 0.15292486 - time (sec): 15.22 - samples/sec: 5399.57 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-18 21:28:18,518 epoch 6 - iter 1188/1984 - loss 0.15391287 - time (sec): 18.07 - samples/sec: 5466.01 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-18 21:28:21,258 epoch 6 - iter 1386/1984 - loss 0.15391731 - time (sec): 20.81 - samples/sec: 5532.31 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-18 21:28:24,192 epoch 6 - iter 1584/1984 - loss 0.15364826 - time (sec): 23.75 - samples/sec: 5517.99 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-18 21:28:27,215 epoch 6 - iter 1782/1984 - loss 0.15355381 - time (sec): 26.77 - samples/sec: 5506.02 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-18 21:28:30,278 epoch 6 - iter 1980/1984 - loss 0.15357759 - time (sec): 29.84 - samples/sec: 5488.25 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-18 21:28:30,343 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:28:30,343 EPOCH 6 done: loss 0.1536 - lr: 0.000022 | |
| 2023-10-18 21:28:32,160 DEV : loss 0.14352329075336456 - f1-score (micro avg) 0.6138 | |
| 2023-10-18 21:28:32,179 saving best model | |
| 2023-10-18 21:28:32,213 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:28:35,313 epoch 7 - iter 198/1984 - loss 0.14010170 - time (sec): 3.10 - samples/sec: 5495.13 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-18 21:28:38,375 epoch 7 - iter 396/1984 - loss 0.14331514 - time (sec): 6.16 - samples/sec: 5523.70 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-18 21:28:41,433 epoch 7 - iter 594/1984 - loss 0.14376651 - time (sec): 9.22 - samples/sec: 5353.76 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-18 21:28:44,525 epoch 7 - iter 792/1984 - loss 0.14327862 - time (sec): 12.31 - samples/sec: 5209.88 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-18 21:28:47,677 epoch 7 - iter 990/1984 - loss 0.14545548 - time (sec): 15.46 - samples/sec: 5195.18 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-18 21:28:50,714 epoch 7 - iter 1188/1984 - loss 0.14341143 - time (sec): 18.50 - samples/sec: 5255.03 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-18 21:28:53,759 epoch 7 - iter 1386/1984 - loss 0.14255578 - time (sec): 21.54 - samples/sec: 5272.56 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-18 21:28:56,904 epoch 7 - iter 1584/1984 - loss 0.14220705 - time (sec): 24.69 - samples/sec: 5262.27 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-18 21:28:59,957 epoch 7 - iter 1782/1984 - loss 0.14227082 - time (sec): 27.74 - samples/sec: 5273.02 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-18 21:29:03,032 epoch 7 - iter 1980/1984 - loss 0.14322288 - time (sec): 30.82 - samples/sec: 5315.07 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-18 21:29:03,091 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:29:03,091 EPOCH 7 done: loss 0.1432 - lr: 0.000017 | |
| 2023-10-18 21:29:04,914 DEV : loss 0.1460934579372406 - f1-score (micro avg) 0.6181 | |
| 2023-10-18 21:29:04,933 saving best model | |
| 2023-10-18 21:29:04,967 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:29:07,991 epoch 8 - iter 198/1984 - loss 0.15508407 - time (sec): 3.02 - samples/sec: 5680.49 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-18 21:29:11,034 epoch 8 - iter 396/1984 - loss 0.14857609 - time (sec): 6.07 - samples/sec: 5447.32 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-18 21:29:14,053 epoch 8 - iter 594/1984 - loss 0.14831674 - time (sec): 9.09 - samples/sec: 5539.95 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-18 21:29:16,965 epoch 8 - iter 792/1984 - loss 0.14431698 - time (sec): 12.00 - samples/sec: 5580.93 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-18 21:29:19,967 epoch 8 - iter 990/1984 - loss 0.14072716 - time (sec): 15.00 - samples/sec: 5527.79 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-18 21:29:23,046 epoch 8 - iter 1188/1984 - loss 0.13730687 - time (sec): 18.08 - samples/sec: 5511.35 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-18 21:29:26,169 epoch 8 - iter 1386/1984 - loss 0.13802672 - time (sec): 21.20 - samples/sec: 5447.35 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-18 21:29:29,261 epoch 8 - iter 1584/1984 - loss 0.13646616 - time (sec): 24.29 - samples/sec: 5454.78 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-18 21:29:32,269 epoch 8 - iter 1782/1984 - loss 0.13626809 - time (sec): 27.30 - samples/sec: 5441.22 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-18 21:29:35,338 epoch 8 - iter 1980/1984 - loss 0.13563883 - time (sec): 30.37 - samples/sec: 5385.09 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-18 21:29:35,401 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:29:35,401 EPOCH 8 done: loss 0.1354 - lr: 0.000011 | |
| 2023-10-18 21:29:37,660 DEV : loss 0.14632448554039001 - f1-score (micro avg) 0.6125 | |
| 2023-10-18 21:29:37,681 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:29:40,791 epoch 9 - iter 198/1984 - loss 0.12436606 - time (sec): 3.11 - samples/sec: 4996.85 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-18 21:29:43,807 epoch 9 - iter 396/1984 - loss 0.12130140 - time (sec): 6.12 - samples/sec: 5243.22 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-18 21:29:46,923 epoch 9 - iter 594/1984 - loss 0.12036860 - time (sec): 9.24 - samples/sec: 5222.59 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-18 21:29:49,986 epoch 9 - iter 792/1984 - loss 0.12390287 - time (sec): 12.30 - samples/sec: 5269.18 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-18 21:29:52,890 epoch 9 - iter 990/1984 - loss 0.12172877 - time (sec): 15.21 - samples/sec: 5357.59 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-18 21:29:55,968 epoch 9 - iter 1188/1984 - loss 0.12359398 - time (sec): 18.29 - samples/sec: 5348.49 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-18 21:29:59,087 epoch 9 - iter 1386/1984 - loss 0.12601590 - time (sec): 21.41 - samples/sec: 5335.60 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-18 21:30:02,163 epoch 9 - iter 1584/1984 - loss 0.12731249 - time (sec): 24.48 - samples/sec: 5329.19 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-18 21:30:05,015 epoch 9 - iter 1782/1984 - loss 0.13000702 - time (sec): 27.33 - samples/sec: 5411.53 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-18 21:30:07,908 epoch 9 - iter 1980/1984 - loss 0.13026706 - time (sec): 30.23 - samples/sec: 5415.84 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-18 21:30:07,967 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:30:07,968 EPOCH 9 done: loss 0.1302 - lr: 0.000006 | |
| 2023-10-18 21:30:09,795 DEV : loss 0.14653360843658447 - f1-score (micro avg) 0.6208 | |
| 2023-10-18 21:30:09,816 saving best model | |
| 2023-10-18 21:30:09,851 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:30:13,178 epoch 10 - iter 198/1984 - loss 0.10287722 - time (sec): 3.33 - samples/sec: 4987.47 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-18 21:30:16,230 epoch 10 - iter 396/1984 - loss 0.11633178 - time (sec): 6.38 - samples/sec: 5153.20 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-18 21:30:19,312 epoch 10 - iter 594/1984 - loss 0.12476201 - time (sec): 9.46 - samples/sec: 5193.09 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-18 21:30:22,352 epoch 10 - iter 792/1984 - loss 0.12536802 - time (sec): 12.50 - samples/sec: 5209.88 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-18 21:30:25,421 epoch 10 - iter 990/1984 - loss 0.12695762 - time (sec): 15.57 - samples/sec: 5294.90 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-18 21:30:28,513 epoch 10 - iter 1188/1984 - loss 0.12707600 - time (sec): 18.66 - samples/sec: 5283.15 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-18 21:30:31,586 epoch 10 - iter 1386/1984 - loss 0.12684283 - time (sec): 21.73 - samples/sec: 5283.84 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-18 21:30:34,749 epoch 10 - iter 1584/1984 - loss 0.12638192 - time (sec): 24.90 - samples/sec: 5252.68 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-18 21:30:37,835 epoch 10 - iter 1782/1984 - loss 0.12660082 - time (sec): 27.98 - samples/sec: 5271.15 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-18 21:30:40,835 epoch 10 - iter 1980/1984 - loss 0.12678588 - time (sec): 30.98 - samples/sec: 5285.51 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-18 21:30:40,894 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:30:40,894 EPOCH 10 done: loss 0.1267 - lr: 0.000000 | |
| 2023-10-18 21:30:42,746 DEV : loss 0.1484779566526413 - f1-score (micro avg) 0.6175 | |
| 2023-10-18 21:30:42,793 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-18 21:30:42,793 Loading model from best epoch ... | |
| 2023-10-18 21:30:42,875 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 | |
| 2023-10-18 21:30:44,397 | |
| Results: | |
| - F-score (micro) 0.6425 | |
| - F-score (macro) 0.4918 | |
| - Accuracy 0.5084 | |
| By class: | |
| precision recall f1-score support | |
| LOC 0.7192 0.7664 0.7421 655 | |
| PER 0.4534 0.6547 0.5358 223 | |
| ORG 0.3778 0.1339 0.1977 127 | |
| micro avg 0.6244 0.6617 0.6425 1005 | |
| macro avg 0.5168 0.5183 0.4918 1005 | |
| weighted avg 0.6171 0.6617 0.6275 1005 | |
| 2023-10-18 21:30:44,397 ---------------------------------------------------------------------------------------------------- | |