| 2023-10-14 09:04:52,387 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:04:52,388 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=13, bias=True) | |
| (loss_function): CrossEntropyLoss() | |
| )" | |
| 2023-10-14 09:04:52,388 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:04:52,388 MultiCorpus: 5777 train + 722 dev + 723 test sentences | |
| - NER_ICDAR_EUROPEANA Corpus: 5777 train + 722 dev + 723 test sentences - /root/.flair/datasets/ner_icdar_europeana/nl | |
| 2023-10-14 09:04:52,388 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:04:52,388 Train: 5777 sentences | |
| 2023-10-14 09:04:52,388 (train_with_dev=False, train_with_test=False) | |
| 2023-10-14 09:04:52,389 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:04:52,389 Training Params: | |
| 2023-10-14 09:04:52,389 - learning_rate: "5e-05" | |
| 2023-10-14 09:04:52,389 - mini_batch_size: "4" | |
| 2023-10-14 09:04:52,389 - max_epochs: "10" | |
| 2023-10-14 09:04:52,389 - shuffle: "True" | |
| 2023-10-14 09:04:52,389 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:04:52,389 Plugins: | |
| 2023-10-14 09:04:52,389 - LinearScheduler | warmup_fraction: '0.1' | |
| 2023-10-14 09:04:52,389 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:04:52,389 Final evaluation on model from best epoch (best-model.pt) | |
| 2023-10-14 09:04:52,389 - metric: "('micro avg', 'f1-score')" | |
| 2023-10-14 09:04:52,389 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:04:52,389 Computation: | |
| 2023-10-14 09:04:52,389 - compute on device: cuda:0 | |
| 2023-10-14 09:04:52,389 - embedding storage: none | |
| 2023-10-14 09:04:52,389 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:04:52,389 Model training base path: "hmbench-icdar/nl-dbmdz/bert-base-historic-multilingual-cased-bs4-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-2" | |
| 2023-10-14 09:04:52,389 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:04:52,389 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:04:59,731 epoch 1 - iter 144/1445 - loss 1.50405988 - time (sec): 7.34 - samples/sec: 2529.66 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-14 09:05:06,888 epoch 1 - iter 288/1445 - loss 0.91392848 - time (sec): 14.50 - samples/sec: 2426.99 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-14 09:05:13,984 epoch 1 - iter 432/1445 - loss 0.69288586 - time (sec): 21.59 - samples/sec: 2402.59 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-14 09:05:21,264 epoch 1 - iter 576/1445 - loss 0.56388054 - time (sec): 28.87 - samples/sec: 2399.95 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-14 09:05:28,714 epoch 1 - iter 720/1445 - loss 0.48076646 - time (sec): 36.32 - samples/sec: 2419.88 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-14 09:05:35,678 epoch 1 - iter 864/1445 - loss 0.42847356 - time (sec): 43.29 - samples/sec: 2427.69 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-14 09:05:43,142 epoch 1 - iter 1008/1445 - loss 0.39150451 - time (sec): 50.75 - samples/sec: 2417.58 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-14 09:05:50,471 epoch 1 - iter 1152/1445 - loss 0.36318531 - time (sec): 58.08 - samples/sec: 2419.76 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-14 09:05:57,811 epoch 1 - iter 1296/1445 - loss 0.33728572 - time (sec): 65.42 - samples/sec: 2423.80 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-14 09:06:04,943 epoch 1 - iter 1440/1445 - loss 0.31810008 - time (sec): 72.55 - samples/sec: 2424.07 - lr: 0.000050 - momentum: 0.000000 | |
| 2023-10-14 09:06:05,168 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:06:05,168 EPOCH 1 done: loss 0.3178 - lr: 0.000050 | |
| 2023-10-14 09:06:08,223 DEV : loss 0.22383828461170197 - f1-score (micro avg) 0.2171 | |
| 2023-10-14 09:06:08,249 saving best model | |
| 2023-10-14 09:06:08,623 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:06:16,873 epoch 2 - iter 144/1445 - loss 0.12739868 - time (sec): 8.25 - samples/sec: 2132.47 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-14 09:06:24,728 epoch 2 - iter 288/1445 - loss 0.12588351 - time (sec): 16.10 - samples/sec: 2237.63 - lr: 0.000049 - momentum: 0.000000 | |
| 2023-10-14 09:06:32,016 epoch 2 - iter 432/1445 - loss 0.12372856 - time (sec): 23.39 - samples/sec: 2310.84 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-14 09:06:39,143 epoch 2 - iter 576/1445 - loss 0.12794083 - time (sec): 30.52 - samples/sec: 2340.94 - lr: 0.000048 - momentum: 0.000000 | |
| 2023-10-14 09:06:46,291 epoch 2 - iter 720/1445 - loss 0.12533257 - time (sec): 37.67 - samples/sec: 2340.89 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-14 09:06:54,019 epoch 2 - iter 864/1445 - loss 0.12315495 - time (sec): 45.39 - samples/sec: 2335.78 - lr: 0.000047 - momentum: 0.000000 | |
| 2023-10-14 09:07:01,101 epoch 2 - iter 1008/1445 - loss 0.11938446 - time (sec): 52.48 - samples/sec: 2351.84 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-14 09:07:08,628 epoch 2 - iter 1152/1445 - loss 0.11944013 - time (sec): 60.00 - samples/sec: 2359.33 - lr: 0.000046 - momentum: 0.000000 | |
| 2023-10-14 09:07:15,760 epoch 2 - iter 1296/1445 - loss 0.11754636 - time (sec): 67.13 - samples/sec: 2367.10 - lr: 0.000045 - momentum: 0.000000 | |
| 2023-10-14 09:07:22,852 epoch 2 - iter 1440/1445 - loss 0.11532296 - time (sec): 74.23 - samples/sec: 2368.20 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-14 09:07:23,072 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:07:23,072 EPOCH 2 done: loss 0.1153 - lr: 0.000044 | |
| 2023-10-14 09:07:26,666 DEV : loss 0.10029048472642899 - f1-score (micro avg) 0.7736 | |
| 2023-10-14 09:07:26,692 saving best model | |
| 2023-10-14 09:07:27,517 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:07:35,649 epoch 3 - iter 144/1445 - loss 0.06660446 - time (sec): 8.13 - samples/sec: 2108.84 - lr: 0.000044 - momentum: 0.000000 | |
| 2023-10-14 09:07:43,714 epoch 3 - iter 288/1445 - loss 0.07183831 - time (sec): 16.19 - samples/sec: 2118.00 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-14 09:07:51,054 epoch 3 - iter 432/1445 - loss 0.07634924 - time (sec): 23.53 - samples/sec: 2189.46 - lr: 0.000043 - momentum: 0.000000 | |
| 2023-10-14 09:07:59,122 epoch 3 - iter 576/1445 - loss 0.08024319 - time (sec): 31.60 - samples/sec: 2280.87 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-14 09:08:06,177 epoch 3 - iter 720/1445 - loss 0.07906010 - time (sec): 38.66 - samples/sec: 2305.52 - lr: 0.000042 - momentum: 0.000000 | |
| 2023-10-14 09:08:13,421 epoch 3 - iter 864/1445 - loss 0.07938145 - time (sec): 45.90 - samples/sec: 2315.39 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-14 09:08:20,731 epoch 3 - iter 1008/1445 - loss 0.07745804 - time (sec): 53.21 - samples/sec: 2331.78 - lr: 0.000041 - momentum: 0.000000 | |
| 2023-10-14 09:08:27,729 epoch 3 - iter 1152/1445 - loss 0.07574091 - time (sec): 60.21 - samples/sec: 2335.63 - lr: 0.000040 - momentum: 0.000000 | |
| 2023-10-14 09:08:34,856 epoch 3 - iter 1296/1445 - loss 0.07435426 - time (sec): 67.34 - samples/sec: 2353.73 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-14 09:08:41,927 epoch 3 - iter 1440/1445 - loss 0.07446722 - time (sec): 74.41 - samples/sec: 2360.70 - lr: 0.000039 - momentum: 0.000000 | |
| 2023-10-14 09:08:42,150 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:08:42,150 EPOCH 3 done: loss 0.0744 - lr: 0.000039 | |
| 2023-10-14 09:08:46,047 DEV : loss 0.11615423113107681 - f1-score (micro avg) 0.778 | |
| 2023-10-14 09:08:46,064 saving best model | |
| 2023-10-14 09:08:46,594 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:08:54,061 epoch 4 - iter 144/1445 - loss 0.05594958 - time (sec): 7.46 - samples/sec: 2420.83 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-14 09:09:01,045 epoch 4 - iter 288/1445 - loss 0.05956758 - time (sec): 14.45 - samples/sec: 2391.16 - lr: 0.000038 - momentum: 0.000000 | |
| 2023-10-14 09:09:08,332 epoch 4 - iter 432/1445 - loss 0.05892843 - time (sec): 21.74 - samples/sec: 2399.08 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-14 09:09:15,764 epoch 4 - iter 576/1445 - loss 0.05643042 - time (sec): 29.17 - samples/sec: 2427.62 - lr: 0.000037 - momentum: 0.000000 | |
| 2023-10-14 09:09:22,692 epoch 4 - iter 720/1445 - loss 0.05466634 - time (sec): 36.10 - samples/sec: 2395.41 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-14 09:09:30,261 epoch 4 - iter 864/1445 - loss 0.05376519 - time (sec): 43.66 - samples/sec: 2414.94 - lr: 0.000036 - momentum: 0.000000 | |
| 2023-10-14 09:09:37,689 epoch 4 - iter 1008/1445 - loss 0.05239450 - time (sec): 51.09 - samples/sec: 2416.84 - lr: 0.000035 - momentum: 0.000000 | |
| 2023-10-14 09:09:45,019 epoch 4 - iter 1152/1445 - loss 0.05246057 - time (sec): 58.42 - samples/sec: 2401.90 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-14 09:09:52,017 epoch 4 - iter 1296/1445 - loss 0.05428593 - time (sec): 65.42 - samples/sec: 2392.09 - lr: 0.000034 - momentum: 0.000000 | |
| 2023-10-14 09:09:59,346 epoch 4 - iter 1440/1445 - loss 0.05316916 - time (sec): 72.75 - samples/sec: 2412.94 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-14 09:09:59,624 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:09:59,624 EPOCH 4 done: loss 0.0530 - lr: 0.000033 | |
| 2023-10-14 09:10:03,275 DEV : loss 0.16486844420433044 - f1-score (micro avg) 0.7972 | |
| 2023-10-14 09:10:03,297 saving best model | |
| 2023-10-14 09:10:03,819 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:10:11,682 epoch 5 - iter 144/1445 - loss 0.04301876 - time (sec): 7.86 - samples/sec: 2266.60 - lr: 0.000033 - momentum: 0.000000 | |
| 2023-10-14 09:10:19,172 epoch 5 - iter 288/1445 - loss 0.04002525 - time (sec): 15.35 - samples/sec: 2415.66 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-14 09:10:27,111 epoch 5 - iter 432/1445 - loss 0.04143923 - time (sec): 23.29 - samples/sec: 2311.89 - lr: 0.000032 - momentum: 0.000000 | |
| 2023-10-14 09:10:34,937 epoch 5 - iter 576/1445 - loss 0.04156500 - time (sec): 31.11 - samples/sec: 2336.56 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-14 09:10:42,201 epoch 5 - iter 720/1445 - loss 0.04080371 - time (sec): 38.38 - samples/sec: 2331.02 - lr: 0.000031 - momentum: 0.000000 | |
| 2023-10-14 09:10:49,603 epoch 5 - iter 864/1445 - loss 0.04181842 - time (sec): 45.78 - samples/sec: 2343.37 - lr: 0.000030 - momentum: 0.000000 | |
| 2023-10-14 09:10:56,781 epoch 5 - iter 1008/1445 - loss 0.04107430 - time (sec): 52.96 - samples/sec: 2351.04 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-14 09:11:04,457 epoch 5 - iter 1152/1445 - loss 0.04027196 - time (sec): 60.63 - samples/sec: 2350.35 - lr: 0.000029 - momentum: 0.000000 | |
| 2023-10-14 09:11:11,722 epoch 5 - iter 1296/1445 - loss 0.04042528 - time (sec): 67.90 - samples/sec: 2343.40 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-14 09:11:18,740 epoch 5 - iter 1440/1445 - loss 0.03984886 - time (sec): 74.92 - samples/sec: 2345.19 - lr: 0.000028 - momentum: 0.000000 | |
| 2023-10-14 09:11:18,993 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:11:18,993 EPOCH 5 done: loss 0.0399 - lr: 0.000028 | |
| 2023-10-14 09:11:22,559 DEV : loss 0.15874287486076355 - f1-score (micro avg) 0.7991 | |
| 2023-10-14 09:11:22,576 saving best model | |
| 2023-10-14 09:11:23,086 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:11:30,207 epoch 6 - iter 144/1445 - loss 0.02521130 - time (sec): 7.12 - samples/sec: 2399.62 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-14 09:11:37,191 epoch 6 - iter 288/1445 - loss 0.02915345 - time (sec): 14.10 - samples/sec: 2371.57 - lr: 0.000027 - momentum: 0.000000 | |
| 2023-10-14 09:11:44,390 epoch 6 - iter 432/1445 - loss 0.02889368 - time (sec): 21.30 - samples/sec: 2397.50 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-14 09:11:51,631 epoch 6 - iter 576/1445 - loss 0.02703670 - time (sec): 28.54 - samples/sec: 2404.49 - lr: 0.000026 - momentum: 0.000000 | |
| 2023-10-14 09:11:59,154 epoch 6 - iter 720/1445 - loss 0.02550238 - time (sec): 36.07 - samples/sec: 2413.63 - lr: 0.000025 - momentum: 0.000000 | |
| 2023-10-14 09:12:06,648 epoch 6 - iter 864/1445 - loss 0.02674173 - time (sec): 43.56 - samples/sec: 2403.51 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-14 09:12:13,801 epoch 6 - iter 1008/1445 - loss 0.02707634 - time (sec): 50.71 - samples/sec: 2404.91 - lr: 0.000024 - momentum: 0.000000 | |
| 2023-10-14 09:12:21,106 epoch 6 - iter 1152/1445 - loss 0.02669468 - time (sec): 58.02 - samples/sec: 2414.59 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-14 09:12:28,455 epoch 6 - iter 1296/1445 - loss 0.02836933 - time (sec): 65.37 - samples/sec: 2419.19 - lr: 0.000023 - momentum: 0.000000 | |
| 2023-10-14 09:12:35,768 epoch 6 - iter 1440/1445 - loss 0.02995850 - time (sec): 72.68 - samples/sec: 2418.03 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-14 09:12:35,987 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:12:35,987 EPOCH 6 done: loss 0.0299 - lr: 0.000022 | |
| 2023-10-14 09:12:39,997 DEV : loss 0.21732811629772186 - f1-score (micro avg) 0.7943 | |
| 2023-10-14 09:12:40,014 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:12:47,625 epoch 7 - iter 144/1445 - loss 0.01983330 - time (sec): 7.61 - samples/sec: 2465.73 - lr: 0.000022 - momentum: 0.000000 | |
| 2023-10-14 09:12:55,063 epoch 7 - iter 288/1445 - loss 0.02159468 - time (sec): 15.05 - samples/sec: 2432.94 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-14 09:13:02,204 epoch 7 - iter 432/1445 - loss 0.02251919 - time (sec): 22.19 - samples/sec: 2420.12 - lr: 0.000021 - momentum: 0.000000 | |
| 2023-10-14 09:13:09,408 epoch 7 - iter 576/1445 - loss 0.02342106 - time (sec): 29.39 - samples/sec: 2410.31 - lr: 0.000020 - momentum: 0.000000 | |
| 2023-10-14 09:13:16,649 epoch 7 - iter 720/1445 - loss 0.02136917 - time (sec): 36.63 - samples/sec: 2420.11 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-14 09:13:24,040 epoch 7 - iter 864/1445 - loss 0.02109943 - time (sec): 44.03 - samples/sec: 2428.59 - lr: 0.000019 - momentum: 0.000000 | |
| 2023-10-14 09:13:31,063 epoch 7 - iter 1008/1445 - loss 0.02065832 - time (sec): 51.05 - samples/sec: 2417.46 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-14 09:13:38,030 epoch 7 - iter 1152/1445 - loss 0.02010615 - time (sec): 58.01 - samples/sec: 2409.33 - lr: 0.000018 - momentum: 0.000000 | |
| 2023-10-14 09:13:45,589 epoch 7 - iter 1296/1445 - loss 0.02234686 - time (sec): 65.57 - samples/sec: 2401.30 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-14 09:13:53,195 epoch 7 - iter 1440/1445 - loss 0.02249980 - time (sec): 73.18 - samples/sec: 2401.41 - lr: 0.000017 - momentum: 0.000000 | |
| 2023-10-14 09:13:53,429 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:13:53,429 EPOCH 7 done: loss 0.0224 - lr: 0.000017 | |
| 2023-10-14 09:13:57,001 DEV : loss 0.17771700024604797 - f1-score (micro avg) 0.8009 | |
| 2023-10-14 09:13:57,019 saving best model | |
| 2023-10-14 09:13:57,654 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:14:04,754 epoch 8 - iter 144/1445 - loss 0.01590043 - time (sec): 7.10 - samples/sec: 2420.47 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-14 09:14:12,074 epoch 8 - iter 288/1445 - loss 0.01595828 - time (sec): 14.42 - samples/sec: 2413.02 - lr: 0.000016 - momentum: 0.000000 | |
| 2023-10-14 09:14:19,826 epoch 8 - iter 432/1445 - loss 0.01610757 - time (sec): 22.17 - samples/sec: 2370.89 - lr: 0.000015 - momentum: 0.000000 | |
| 2023-10-14 09:14:27,167 epoch 8 - iter 576/1445 - loss 0.01647436 - time (sec): 29.51 - samples/sec: 2362.40 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-14 09:14:34,347 epoch 8 - iter 720/1445 - loss 0.01689704 - time (sec): 36.69 - samples/sec: 2370.89 - lr: 0.000014 - momentum: 0.000000 | |
| 2023-10-14 09:14:41,943 epoch 8 - iter 864/1445 - loss 0.01595512 - time (sec): 44.29 - samples/sec: 2366.99 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-14 09:14:49,142 epoch 8 - iter 1008/1445 - loss 0.01521523 - time (sec): 51.49 - samples/sec: 2373.12 - lr: 0.000013 - momentum: 0.000000 | |
| 2023-10-14 09:14:56,752 epoch 8 - iter 1152/1445 - loss 0.01566291 - time (sec): 59.10 - samples/sec: 2374.23 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-14 09:15:04,136 epoch 8 - iter 1296/1445 - loss 0.01524212 - time (sec): 66.48 - samples/sec: 2380.20 - lr: 0.000012 - momentum: 0.000000 | |
| 2023-10-14 09:15:11,600 epoch 8 - iter 1440/1445 - loss 0.01548357 - time (sec): 73.94 - samples/sec: 2374.29 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-14 09:15:11,887 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:15:11,887 EPOCH 8 done: loss 0.0157 - lr: 0.000011 | |
| 2023-10-14 09:15:15,393 DEV : loss 0.18877749145030975 - f1-score (micro avg) 0.8117 | |
| 2023-10-14 09:15:15,410 saving best model | |
| 2023-10-14 09:15:15,872 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:15:24,218 epoch 9 - iter 144/1445 - loss 0.01359555 - time (sec): 8.34 - samples/sec: 2153.76 - lr: 0.000011 - momentum: 0.000000 | |
| 2023-10-14 09:15:32,316 epoch 9 - iter 288/1445 - loss 0.01054503 - time (sec): 16.44 - samples/sec: 2214.35 - lr: 0.000010 - momentum: 0.000000 | |
| 2023-10-14 09:15:40,564 epoch 9 - iter 432/1445 - loss 0.01149262 - time (sec): 24.69 - samples/sec: 2159.06 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-14 09:15:48,781 epoch 9 - iter 576/1445 - loss 0.00991121 - time (sec): 32.91 - samples/sec: 2155.60 - lr: 0.000009 - momentum: 0.000000 | |
| 2023-10-14 09:15:57,145 epoch 9 - iter 720/1445 - loss 0.01022072 - time (sec): 41.27 - samples/sec: 2165.38 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-14 09:16:05,349 epoch 9 - iter 864/1445 - loss 0.01065988 - time (sec): 49.47 - samples/sec: 2175.46 - lr: 0.000008 - momentum: 0.000000 | |
| 2023-10-14 09:16:13,454 epoch 9 - iter 1008/1445 - loss 0.01047689 - time (sec): 57.58 - samples/sec: 2176.55 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-14 09:16:21,315 epoch 9 - iter 1152/1445 - loss 0.01036723 - time (sec): 65.44 - samples/sec: 2165.04 - lr: 0.000007 - momentum: 0.000000 | |
| 2023-10-14 09:16:29,408 epoch 9 - iter 1296/1445 - loss 0.01166652 - time (sec): 73.53 - samples/sec: 2169.75 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-14 09:16:37,351 epoch 9 - iter 1440/1445 - loss 0.01098843 - time (sec): 81.48 - samples/sec: 2156.71 - lr: 0.000006 - momentum: 0.000000 | |
| 2023-10-14 09:16:37,608 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:16:37,608 EPOCH 9 done: loss 0.0110 - lr: 0.000006 | |
| 2023-10-14 09:16:41,539 DEV : loss 0.20204880833625793 - f1-score (micro avg) 0.8105 | |
| 2023-10-14 09:16:41,555 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:16:48,967 epoch 10 - iter 144/1445 - loss 0.00491564 - time (sec): 7.41 - samples/sec: 2411.29 - lr: 0.000005 - momentum: 0.000000 | |
| 2023-10-14 09:16:56,199 epoch 10 - iter 288/1445 - loss 0.00600497 - time (sec): 14.64 - samples/sec: 2387.86 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-14 09:17:03,075 epoch 10 - iter 432/1445 - loss 0.00613285 - time (sec): 21.52 - samples/sec: 2398.58 - lr: 0.000004 - momentum: 0.000000 | |
| 2023-10-14 09:17:10,266 epoch 10 - iter 576/1445 - loss 0.00629679 - time (sec): 28.71 - samples/sec: 2427.46 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-14 09:17:17,507 epoch 10 - iter 720/1445 - loss 0.00605855 - time (sec): 35.95 - samples/sec: 2413.82 - lr: 0.000003 - momentum: 0.000000 | |
| 2023-10-14 09:17:24,864 epoch 10 - iter 864/1445 - loss 0.00744087 - time (sec): 43.31 - samples/sec: 2421.84 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-14 09:17:32,104 epoch 10 - iter 1008/1445 - loss 0.00687721 - time (sec): 50.55 - samples/sec: 2429.28 - lr: 0.000002 - momentum: 0.000000 | |
| 2023-10-14 09:17:39,595 epoch 10 - iter 1152/1445 - loss 0.00728344 - time (sec): 58.04 - samples/sec: 2427.34 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-14 09:17:46,851 epoch 10 - iter 1296/1445 - loss 0.00674719 - time (sec): 65.29 - samples/sec: 2431.63 - lr: 0.000001 - momentum: 0.000000 | |
| 2023-10-14 09:17:53,975 epoch 10 - iter 1440/1445 - loss 0.00726142 - time (sec): 72.42 - samples/sec: 2425.99 - lr: 0.000000 - momentum: 0.000000 | |
| 2023-10-14 09:17:54,218 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:17:54,218 EPOCH 10 done: loss 0.0072 - lr: 0.000000 | |
| 2023-10-14 09:17:57,706 DEV : loss 0.20339810848236084 - f1-score (micro avg) 0.822 | |
| 2023-10-14 09:17:57,722 saving best model | |
| 2023-10-14 09:17:58,576 ---------------------------------------------------------------------------------------------------- | |
| 2023-10-14 09:17:58,577 Loading model from best epoch ... | |
| 2023-10-14 09:18:00,174 SequenceTagger predicts: Dictionary with 13 tags: O, S-LOC, B-LOC, E-LOC, I-LOC, S-PER, B-PER, E-PER, I-PER, S-ORG, B-ORG, E-ORG, I-ORG | |
| 2023-10-14 09:18:03,299 | |
| Results: | |
| - F-score (micro) 0.7921 | |
| - F-score (macro) 0.6958 | |
| - Accuracy 0.6684 | |
| By class: | |
| precision recall f1-score support | |
| PER 0.8134 0.7780 0.7953 482 | |
| LOC 0.8864 0.7838 0.8320 458 | |
| ORG 0.5909 0.3768 0.4602 69 | |
| micro avg 0.8352 0.7532 0.7921 1009 | |
| macro avg 0.7636 0.6462 0.6958 1009 | |
| weighted avg 0.8314 0.7532 0.7890 1009 | |
| 2023-10-14 09:18:03,300 ---------------------------------------------------------------------------------------------------- | |