| 2023-09-03 19:44:59,244 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:44:59,245 Model: "SequenceTagger( | |
| (embeddings): TransformerWordEmbeddings( | |
| (model): BertModel( | |
| (embeddings): BertEmbeddings( | |
| (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): BertEncoder( | |
| (layer): ModuleList( | |
| (0-11): 12 x BertLayer( | |
| (attention): BertAttention( | |
| (self): BertSelfAttention( | |
| (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): BertSelfOutput( | |
| (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): BertIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| (intermediate_act_fn): GELUActivation() | |
| ) | |
| (output): BertOutput( | |
| (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) | |
| ) | |
| ) | |
| ) | |
| ) | |
| (pooler): BertPooler( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (activation): Tanh() | |
| ) | |
| ) | |
| ) | |
| (locked_dropout): LockedDropout(p=0.5) | |
| (linear): Linear(in_features=768, out_features=21, bias=True) | |
| (loss_function): CrossEntropyLoss() | |
| )" | |
| 2023-09-03 19:44:59,245 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:44:59,246 MultiCorpus: 3575 train + 1235 dev + 1266 test sentences | |
| - NER_HIPE_2022 Corpus: 3575 train + 1235 dev + 1266 test sentences - /app/.flair/datasets/ner_hipe_2022/v2.1/hipe2020/de/with_doc_seperator | |
| 2023-09-03 19:44:59,246 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:44:59,246 Train: 3575 sentences | |
| 2023-09-03 19:44:59,246 (train_with_dev=False, train_with_test=False) | |
| 2023-09-03 19:44:59,246 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:44:59,246 Training Params: | |
| 2023-09-03 19:44:59,246 - learning_rate: "5e-05" | |
| 2023-09-03 19:44:59,246 - mini_batch_size: "8" | |
| 2023-09-03 19:44:59,246 - max_epochs: "10" | |
| 2023-09-03 19:44:59,246 - shuffle: "True" | |
| 2023-09-03 19:44:59,246 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:44:59,246 Plugins: | |
| 2023-09-03 19:44:59,246 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-09-03 19:44:59,246 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:44:59,246 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-09-03 19:44:59,246 - metric: "('micro avg', 'f1-score')" | |
| 2023-09-03 19:44:59,247 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:44:59,247 Computation: | |
| 2023-09-03 19:44:59,247 - compute on device: cuda:0 | |
| 2023-09-03 19:44:59,247 - embedding storage: none | |
| 2023-09-03 19:44:59,247 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:44:59,247 Model training base path: "hmbench-hipe2020/de-dbmdz/bert-base-historic-multilingual-cased-bs8-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-2" | |
| 2023-09-03 19:44:59,247 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:44:59,247 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:45:05,857 epoch 1 - iter 44/447 - loss 3.05895178 - time (sec): 6.61 - samples/sec: 1206.22 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-09-03 19:45:12,691 epoch 1 - iter 88/447 - loss 2.11073299 - time (sec): 13.44 - samples/sec: 1185.47 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-09-03 19:45:19,769 epoch 1 - iter 132/447 - loss 1.51691462 - time (sec): 20.52 - samples/sec: 1203.61 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-09-03 19:45:26,516 epoch 1 - iter 176/447 - loss 1.24634762 - time (sec): 27.27 - samples/sec: 1196.86 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-09-03 19:45:33,690 epoch 1 - iter 220/447 - loss 1.05616858 - time (sec): 34.44 - samples/sec: 1197.99 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-09-03 19:45:42,842 epoch 1 - iter 264/447 - loss 0.91207757 - time (sec): 43.59 - samples/sec: 1184.02 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-09-03 19:45:50,353 epoch 1 - iter 308/447 - loss 0.82591020 - time (sec): 51.11 - samples/sec: 1166.61 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-09-03 19:45:57,145 epoch 1 - iter 352/447 - loss 0.75411732 - time (sec): 57.90 - samples/sec: 1175.35 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-09-03 19:46:04,586 epoch 1 - iter 396/447 - loss 0.69733732 - time (sec): 65.34 - samples/sec: 1169.96 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-09-03 19:46:11,651 epoch 1 - iter 440/447 - loss 0.65001169 - time (sec): 72.40 - samples/sec: 1169.08 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-09-03 19:46:13,120 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:46:13,120 EPOCH 1 done: loss 0.6402 - lr: 0.000049 | |
| 2023-09-03 19:46:23,336 DEV : loss 0.17735987901687622 - f1-score (micro avg) 0.5967 | |
| 2023-09-03 19:46:23,362 saving best model | |
| 2023-09-03 19:46:23,836 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:46:31,012 epoch 2 - iter 44/447 - loss 0.20544633 - time (sec): 7.17 - samples/sec: 1187.90 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-09-03 19:46:38,511 epoch 2 - iter 88/447 - loss 0.18673012 - time (sec): 14.67 - samples/sec: 1149.88 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-09-03 19:46:45,256 epoch 2 - iter 132/447 - loss 0.17694085 - time (sec): 21.42 - samples/sec: 1167.73 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-09-03 19:46:52,651 epoch 2 - iter 176/447 - loss 0.17433877 - time (sec): 28.81 - samples/sec: 1172.35 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-09-03 19:46:59,416 epoch 2 - iter 220/447 - loss 0.16657912 - time (sec): 35.58 - samples/sec: 1168.52 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-09-03 19:47:07,929 epoch 2 - iter 264/447 - loss 0.16283126 - time (sec): 44.09 - samples/sec: 1154.74 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-09-03 19:47:14,974 epoch 2 - iter 308/447 - loss 0.15741588 - time (sec): 51.14 - samples/sec: 1158.92 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-09-03 19:47:22,920 epoch 2 - iter 352/447 - loss 0.15314425 - time (sec): 59.08 - samples/sec: 1160.86 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-09-03 19:47:30,918 epoch 2 - iter 396/447 - loss 0.15205093 - time (sec): 67.08 - samples/sec: 1147.38 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-09-03 19:47:38,144 epoch 2 - iter 440/447 - loss 0.15048232 - time (sec): 74.31 - samples/sec: 1147.07 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-09-03 19:47:39,160 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:47:39,160 EPOCH 2 done: loss 0.1503 - lr: 0.000045 | |
| 2023-09-03 19:47:51,877 DEV : loss 0.12148022651672363 - f1-score (micro avg) 0.6901 | |
| 2023-09-03 19:47:51,904 saving best model | |
| 2023-09-03 19:47:53,220 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:48:01,161 epoch 3 - iter 44/447 - loss 0.09924091 - time (sec): 7.94 - samples/sec: 1072.62 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-09-03 19:48:09,418 epoch 3 - iter 88/447 - loss 0.08969886 - time (sec): 16.20 - samples/sec: 1118.01 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-09-03 19:48:17,460 epoch 3 - iter 132/447 - loss 0.09047889 - time (sec): 24.24 - samples/sec: 1123.80 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-09-03 19:48:25,295 epoch 3 - iter 176/447 - loss 0.08321965 - time (sec): 32.07 - samples/sec: 1126.69 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-09-03 19:48:33,299 epoch 3 - iter 220/447 - loss 0.08905560 - time (sec): 40.08 - samples/sec: 1123.12 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-09-03 19:48:40,616 epoch 3 - iter 264/447 - loss 0.08981123 - time (sec): 47.39 - samples/sec: 1110.01 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-09-03 19:48:47,565 epoch 3 - iter 308/447 - loss 0.08795390 - time (sec): 54.34 - samples/sec: 1119.05 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-09-03 19:48:54,505 epoch 3 - iter 352/447 - loss 0.08610301 - time (sec): 61.28 - samples/sec: 1123.02 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-09-03 19:49:02,184 epoch 3 - iter 396/447 - loss 0.08514806 - time (sec): 68.96 - samples/sec: 1118.00 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-09-03 19:49:09,340 epoch 3 - iter 440/447 - loss 0.08672027 - time (sec): 76.12 - samples/sec: 1120.18 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-09-03 19:49:10,414 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:49:10,415 EPOCH 3 done: loss 0.0869 - lr: 0.000039 | |
| 2023-09-03 19:49:23,440 DEV : loss 0.14279478788375854 - f1-score (micro avg) 0.7312 | |
| 2023-09-03 19:49:23,466 saving best model | |
| 2023-09-03 19:49:24,811 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:49:31,483 epoch 4 - iter 44/447 - loss 0.05469815 - time (sec): 6.67 - samples/sec: 1132.40 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-09-03 19:49:39,956 epoch 4 - iter 88/447 - loss 0.04959434 - time (sec): 15.14 - samples/sec: 1110.71 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-09-03 19:49:47,478 epoch 4 - iter 132/447 - loss 0.05492602 - time (sec): 22.67 - samples/sec: 1106.59 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-09-03 19:49:54,970 epoch 4 - iter 176/447 - loss 0.05135116 - time (sec): 30.16 - samples/sec: 1115.21 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-09-03 19:50:01,928 epoch 4 - iter 220/447 - loss 0.05098197 - time (sec): 37.12 - samples/sec: 1106.13 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-09-03 19:50:11,049 epoch 4 - iter 264/447 - loss 0.04879327 - time (sec): 46.24 - samples/sec: 1103.35 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-09-03 19:50:19,900 epoch 4 - iter 308/447 - loss 0.04932569 - time (sec): 55.09 - samples/sec: 1085.19 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-09-03 19:50:27,153 epoch 4 - iter 352/447 - loss 0.04866242 - time (sec): 62.34 - samples/sec: 1088.19 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-09-03 19:50:35,195 epoch 4 - iter 396/447 - loss 0.04767351 - time (sec): 70.38 - samples/sec: 1095.46 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-09-03 19:50:42,562 epoch 4 - iter 440/447 - loss 0.04931913 - time (sec): 77.75 - samples/sec: 1097.96 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-09-03 19:50:43,634 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:50:43,635 EPOCH 4 done: loss 0.0489 - lr: 0.000033 | |
| 2023-09-03 19:50:57,187 DEV : loss 0.1648201197385788 - f1-score (micro avg) 0.7606 | |
| 2023-09-03 19:50:57,213 saving best model | |
| 2023-09-03 19:50:58,556 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:51:06,145 epoch 5 - iter 44/447 - loss 0.05705444 - time (sec): 7.59 - samples/sec: 1065.57 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-09-03 19:51:13,447 epoch 5 - iter 88/447 - loss 0.04319302 - time (sec): 14.89 - samples/sec: 1067.09 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-09-03 19:51:21,475 epoch 5 - iter 132/447 - loss 0.03634302 - time (sec): 22.92 - samples/sec: 1069.66 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-09-03 19:51:28,956 epoch 5 - iter 176/447 - loss 0.03666310 - time (sec): 30.40 - samples/sec: 1074.08 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-09-03 19:51:37,660 epoch 5 - iter 220/447 - loss 0.03444196 - time (sec): 39.10 - samples/sec: 1087.00 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-09-03 19:51:44,587 epoch 5 - iter 264/447 - loss 0.03435495 - time (sec): 46.03 - samples/sec: 1104.34 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-09-03 19:51:52,881 epoch 5 - iter 308/447 - loss 0.03424624 - time (sec): 54.32 - samples/sec: 1100.18 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-09-03 19:52:01,766 epoch 5 - iter 352/447 - loss 0.03319613 - time (sec): 63.21 - samples/sec: 1092.33 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-09-03 19:52:09,298 epoch 5 - iter 396/447 - loss 0.03312079 - time (sec): 70.74 - samples/sec: 1098.90 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-09-03 19:52:15,926 epoch 5 - iter 440/447 - loss 0.03388957 - time (sec): 77.37 - samples/sec: 1101.65 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-09-03 19:52:17,020 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:52:17,020 EPOCH 5 done: loss 0.0335 - lr: 0.000028 | |
| 2023-09-03 19:52:30,551 DEV : loss 0.17944809794425964 - f1-score (micro avg) 0.7624 | |
| 2023-09-03 19:52:30,577 saving best model | |
| 2023-09-03 19:52:31,909 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:52:39,597 epoch 6 - iter 44/447 - loss 0.02485402 - time (sec): 7.69 - samples/sec: 1116.90 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-09-03 19:52:47,114 epoch 6 - iter 88/447 - loss 0.02547663 - time (sec): 15.20 - samples/sec: 1103.64 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-09-03 19:52:54,357 epoch 6 - iter 132/447 - loss 0.02496451 - time (sec): 22.45 - samples/sec: 1105.73 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-09-03 19:53:01,908 epoch 6 - iter 176/447 - loss 0.02252033 - time (sec): 30.00 - samples/sec: 1105.92 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-09-03 19:53:09,954 epoch 6 - iter 220/447 - loss 0.02461582 - time (sec): 38.04 - samples/sec: 1093.96 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-09-03 19:53:17,244 epoch 6 - iter 264/447 - loss 0.02321987 - time (sec): 45.33 - samples/sec: 1102.08 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-09-03 19:53:24,181 epoch 6 - iter 308/447 - loss 0.02317291 - time (sec): 52.27 - samples/sec: 1106.26 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-09-03 19:53:32,115 epoch 6 - iter 352/447 - loss 0.02274179 - time (sec): 60.20 - samples/sec: 1103.52 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-09-03 19:53:40,466 epoch 6 - iter 396/447 - loss 0.02264507 - time (sec): 68.56 - samples/sec: 1094.47 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-09-03 19:53:49,679 epoch 6 - iter 440/447 - loss 0.02271494 - time (sec): 77.77 - samples/sec: 1093.16 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-09-03 19:53:51,045 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:53:51,045 EPOCH 6 done: loss 0.0225 - lr: 0.000022 | |
| 2023-09-03 19:54:04,567 DEV : loss 0.20019599795341492 - f1-score (micro avg) 0.7655 | |
| 2023-09-03 19:54:04,597 saving best model | |
| 2023-09-03 19:54:05,905 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:54:13,458 epoch 7 - iter 44/447 - loss 0.01666146 - time (sec): 7.55 - samples/sec: 1139.14 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-09-03 19:54:21,169 epoch 7 - iter 88/447 - loss 0.01354020 - time (sec): 15.26 - samples/sec: 1120.25 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-09-03 19:54:28,391 epoch 7 - iter 132/447 - loss 0.01334057 - time (sec): 22.49 - samples/sec: 1161.60 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-09-03 19:54:36,296 epoch 7 - iter 176/447 - loss 0.01659884 - time (sec): 30.39 - samples/sec: 1144.50 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-09-03 19:54:43,739 epoch 7 - iter 220/447 - loss 0.01532998 - time (sec): 37.83 - samples/sec: 1129.04 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-09-03 19:54:51,605 epoch 7 - iter 264/447 - loss 0.01415707 - time (sec): 45.70 - samples/sec: 1124.83 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-09-03 19:54:59,015 epoch 7 - iter 308/447 - loss 0.01444906 - time (sec): 53.11 - samples/sec: 1119.15 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-09-03 19:55:06,627 epoch 7 - iter 352/447 - loss 0.01551328 - time (sec): 60.72 - samples/sec: 1117.77 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-09-03 19:55:13,724 epoch 7 - iter 396/447 - loss 0.01473543 - time (sec): 67.82 - samples/sec: 1112.82 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-09-03 19:55:22,391 epoch 7 - iter 440/447 - loss 0.01420854 - time (sec): 76.49 - samples/sec: 1106.37 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-09-03 19:55:24,456 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:55:24,456 EPOCH 7 done: loss 0.0143 - lr: 0.000017 | |
| 2023-09-03 19:55:37,962 DEV : loss 0.2281445562839508 - f1-score (micro avg) 0.7771 | |
| 2023-09-03 19:55:37,989 saving best model | |
| 2023-09-03 19:55:39,292 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:55:46,351 epoch 8 - iter 44/447 - loss 0.00442347 - time (sec): 7.06 - samples/sec: 1182.60 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-09-03 19:55:56,134 epoch 8 - iter 88/447 - loss 0.00807419 - time (sec): 16.84 - samples/sec: 1060.16 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-09-03 19:56:03,654 epoch 8 - iter 132/447 - loss 0.01003653 - time (sec): 24.36 - samples/sec: 1071.34 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-09-03 19:56:10,984 epoch 8 - iter 176/447 - loss 0.00929882 - time (sec): 31.69 - samples/sec: 1089.54 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-09-03 19:56:18,155 epoch 8 - iter 220/447 - loss 0.00972771 - time (sec): 38.86 - samples/sec: 1091.29 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-09-03 19:56:26,590 epoch 8 - iter 264/447 - loss 0.00984762 - time (sec): 47.30 - samples/sec: 1082.78 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-09-03 19:56:34,284 epoch 8 - iter 308/447 - loss 0.01092729 - time (sec): 54.99 - samples/sec: 1092.57 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-09-03 19:56:41,737 epoch 8 - iter 352/447 - loss 0.01138641 - time (sec): 62.44 - samples/sec: 1092.31 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-09-03 19:56:49,454 epoch 8 - iter 396/447 - loss 0.01142584 - time (sec): 70.16 - samples/sec: 1094.14 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-09-03 19:56:57,103 epoch 8 - iter 440/447 - loss 0.01077808 - time (sec): 77.81 - samples/sec: 1095.66 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-09-03 19:56:58,265 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:56:58,265 EPOCH 8 done: loss 0.0106 - lr: 0.000011 | |
| 2023-09-03 19:57:11,784 DEV : loss 0.23382732272148132 - f1-score (micro avg) 0.7852 | |
| 2023-09-03 19:57:11,811 saving best model | |
| 2023-09-03 19:57:13,138 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:57:20,737 epoch 9 - iter 44/447 - loss 0.00165931 - time (sec): 7.60 - samples/sec: 1126.33 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-09-03 19:57:27,693 epoch 9 - iter 88/447 - loss 0.00338486 - time (sec): 14.55 - samples/sec: 1156.33 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-09-03 19:57:35,368 epoch 9 - iter 132/447 - loss 0.00456257 - time (sec): 22.23 - samples/sec: 1126.60 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-09-03 19:57:42,847 epoch 9 - iter 176/447 - loss 0.00458564 - time (sec): 29.71 - samples/sec: 1133.33 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-09-03 19:57:52,291 epoch 9 - iter 220/447 - loss 0.00481797 - time (sec): 39.15 - samples/sec: 1106.53 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-09-03 19:57:59,739 epoch 9 - iter 264/447 - loss 0.00481335 - time (sec): 46.60 - samples/sec: 1110.30 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-09-03 19:58:07,268 epoch 9 - iter 308/447 - loss 0.00589621 - time (sec): 54.13 - samples/sec: 1104.51 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-09-03 19:58:15,233 epoch 9 - iter 352/447 - loss 0.00584651 - time (sec): 62.09 - samples/sec: 1107.37 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-09-03 19:58:22,095 epoch 9 - iter 396/447 - loss 0.00623178 - time (sec): 68.96 - samples/sec: 1111.26 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-09-03 19:58:29,284 epoch 9 - iter 440/447 - loss 0.00617847 - time (sec): 76.14 - samples/sec: 1117.26 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-09-03 19:58:31,053 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:58:31,054 EPOCH 9 done: loss 0.0063 - lr: 0.000006 | |
| 2023-09-03 19:58:43,941 DEV : loss 0.2306753247976303 - f1-score (micro avg) 0.7844 | |
| 2023-09-03 19:58:43,968 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:58:51,779 epoch 10 - iter 44/447 - loss 0.00222028 - time (sec): 7.81 - samples/sec: 1171.46 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-09-03 19:58:58,749 epoch 10 - iter 88/447 - loss 0.00444802 - time (sec): 14.78 - samples/sec: 1161.23 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-09-03 19:59:06,006 epoch 10 - iter 132/447 - loss 0.00413128 - time (sec): 22.04 - samples/sec: 1150.68 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-09-03 19:59:14,713 epoch 10 - iter 176/447 - loss 0.00339273 - time (sec): 30.74 - samples/sec: 1147.16 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-09-03 19:59:21,550 epoch 10 - iter 220/447 - loss 0.00445031 - time (sec): 37.58 - samples/sec: 1157.95 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-09-03 19:59:28,080 epoch 10 - iter 264/447 - loss 0.00448787 - time (sec): 44.11 - samples/sec: 1173.73 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-09-03 19:59:34,811 epoch 10 - iter 308/447 - loss 0.00440139 - time (sec): 50.84 - samples/sec: 1171.05 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-09-03 19:59:42,765 epoch 10 - iter 352/447 - loss 0.00399426 - time (sec): 58.79 - samples/sec: 1160.10 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-09-03 19:59:49,844 epoch 10 - iter 396/447 - loss 0.00395381 - time (sec): 65.87 - samples/sec: 1158.72 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-09-03 19:59:57,688 epoch 10 - iter 440/447 - loss 0.00420395 - time (sec): 73.72 - samples/sec: 1158.44 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-09-03 19:59:58,758 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 19:59:58,758 EPOCH 10 done: loss 0.0041 - lr: 0.000000 | |
| 2023-09-03 20:00:11,492 DEV : loss 0.2330584079027176 - f1-score (micro avg) 0.7858 | |
| 2023-09-03 20:00:11,520 saving best model | |
| 2023-09-03 20:00:13,308 ---------------------------------------------------------------------------------------------------- | |
| 2023-09-03 20:00:13,309 Loading model from best epoch ... | |
| 2023-09-03 20:00:15,075 SequenceTagger predicts: Dictionary with 21 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, S-prod, B-prod, E-prod, I-prod, S-time, B-time, E-time, I-time | |
| 2023-09-03 20:00:24,956 | |
| Results: | |
| - F-score (micro) 0.7411 | |
| - F-score (macro) 0.6789 | |
| - Accuracy 0.6072 | |
| By class: | |
| precision recall f1-score support | |
| loc 0.8114 0.8372 0.8241 596 | |
| pers 0.6623 0.7538 0.7051 333 | |
| org 0.5285 0.4924 0.5098 132 | |
| prod 0.6415 0.5152 0.5714 66 | |
| time 0.7547 0.8163 0.7843 49 | |
| micro avg 0.7269 0.7560 0.7411 1176 | |
| macro avg 0.6797 0.6830 0.6789 1176 | |
| weighted avg 0.7255 0.7560 0.7393 1176 | |
| 2023-09-03 20:00:24,956 ---------------------------------------------------------------------------------------------------- | |