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2023-10-14 10:43:55,873 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:43:55,874 Model: "SequenceTagger( |
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(embeddings): TransformerWordEmbeddings( |
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(model): BertModel( |
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(embeddings): BertEmbeddings( |
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(word_embeddings): Embedding(32001, 768) |
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(position_embeddings): Embedding(512, 768) |
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(token_type_embeddings): Embedding(2, 768) |
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(LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) |
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(dropout): Dropout(p=0.1, inplace=False) |
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) |
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(encoder): BertEncoder( |
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(layer): ModuleList( |
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(0-11): 12 x BertLayer( |
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(attention): BertAttention( |
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(self): BertSelfAttention( |
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(query): Linear(in_features=768, out_features=768, bias=True) |
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(key): Linear(in_features=768, out_features=768, bias=True) |
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(value): Linear(in_features=768, out_features=768, bias=True) |
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(dropout): Dropout(p=0.1, inplace=False) |
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) |
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(output): BertSelfOutput( |
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(dense): Linear(in_features=768, out_features=768, bias=True) |
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(LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) |
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(dropout): Dropout(p=0.1, inplace=False) |
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) |
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) |
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(intermediate): BertIntermediate( |
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(dense): Linear(in_features=768, out_features=3072, bias=True) |
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(intermediate_act_fn): GELUActivation() |
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) |
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(output): BertOutput( |
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(dense): Linear(in_features=3072, out_features=768, bias=True) |
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(LayerNorm): LayerNorm((768,), eps=1e-12, elementwise_affine=True) |
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(dropout): Dropout(p=0.1, inplace=False) |
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) |
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) |
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) |
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) |
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(pooler): BertPooler( |
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(dense): Linear(in_features=768, out_features=768, bias=True) |
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(activation): Tanh() |
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) |
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) |
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) |
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(locked_dropout): LockedDropout(p=0.5) |
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(linear): Linear(in_features=768, out_features=13, bias=True) |
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(loss_function): CrossEntropyLoss() |
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)" |
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2023-10-14 10:43:55,874 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:43:55,874 MultiCorpus: 5777 train + 722 dev + 723 test sentences |
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- NER_ICDAR_EUROPEANA Corpus: 5777 train + 722 dev + 723 test sentences - /root/.flair/datasets/ner_icdar_europeana/nl |
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2023-10-14 10:43:55,874 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:43:55,874 Train: 5777 sentences |
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2023-10-14 10:43:55,874 (train_with_dev=False, train_with_test=False) |
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2023-10-14 10:43:55,874 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:43:55,875 Training Params: |
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2023-10-14 10:43:55,875 - learning_rate: "5e-05" |
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2023-10-14 10:43:55,875 - mini_batch_size: "4" |
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2023-10-14 10:43:55,875 - max_epochs: "10" |
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2023-10-14 10:43:55,875 - shuffle: "True" |
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2023-10-14 10:43:55,875 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:43:55,875 Plugins: |
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2023-10-14 10:43:55,875 - LinearScheduler | warmup_fraction: '0.1' |
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2023-10-14 10:43:55,875 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:43:55,875 Final evaluation on model from best epoch (best-model.pt) |
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2023-10-14 10:43:55,875 - metric: "('micro avg', 'f1-score')" |
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2023-10-14 10:43:55,875 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:43:55,875 Computation: |
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2023-10-14 10:43:55,875 - compute on device: cuda:0 |
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2023-10-14 10:43:55,875 - embedding storage: none |
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2023-10-14 10:43:55,875 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:43:55,875 Model training base path: "hmbench-icdar/nl-dbmdz/bert-base-historic-multilingual-cased-bs4-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-4" |
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2023-10-14 10:43:55,875 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:43:55,875 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:44:03,371 epoch 1 - iter 144/1445 - loss 1.53614842 - time (sec): 7.49 - samples/sec: 2488.14 - lr: 0.000005 - momentum: 0.000000 |
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2023-10-14 10:44:10,666 epoch 1 - iter 288/1445 - loss 0.92543100 - time (sec): 14.79 - samples/sec: 2442.39 - lr: 0.000010 - momentum: 0.000000 |
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2023-10-14 10:44:18,047 epoch 1 - iter 432/1445 - loss 0.68772860 - time (sec): 22.17 - samples/sec: 2403.60 - lr: 0.000015 - momentum: 0.000000 |
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2023-10-14 10:44:25,279 epoch 1 - iter 576/1445 - loss 0.56173958 - time (sec): 29.40 - samples/sec: 2387.31 - lr: 0.000020 - momentum: 0.000000 |
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2023-10-14 10:44:32,595 epoch 1 - iter 720/1445 - loss 0.47974609 - time (sec): 36.72 - samples/sec: 2404.37 - lr: 0.000025 - momentum: 0.000000 |
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2023-10-14 10:44:39,880 epoch 1 - iter 864/1445 - loss 0.42590462 - time (sec): 44.00 - samples/sec: 2411.14 - lr: 0.000030 - momentum: 0.000000 |
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2023-10-14 10:44:47,180 epoch 1 - iter 1008/1445 - loss 0.38604397 - time (sec): 51.30 - samples/sec: 2409.43 - lr: 0.000035 - momentum: 0.000000 |
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2023-10-14 10:44:54,827 epoch 1 - iter 1152/1445 - loss 0.35511393 - time (sec): 58.95 - samples/sec: 2419.50 - lr: 0.000040 - momentum: 0.000000 |
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2023-10-14 10:45:01,879 epoch 1 - iter 1296/1445 - loss 0.33007466 - time (sec): 66.00 - samples/sec: 2423.12 - lr: 0.000045 - momentum: 0.000000 |
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2023-10-14 10:45:08,740 epoch 1 - iter 1440/1445 - loss 0.31318374 - time (sec): 72.86 - samples/sec: 2410.77 - lr: 0.000050 - momentum: 0.000000 |
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2023-10-14 10:45:08,985 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:45:08,986 EPOCH 1 done: loss 0.3125 - lr: 0.000050 |
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2023-10-14 10:45:12,844 DEV : loss 0.1323496401309967 - f1-score (micro avg) 0.6425 |
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2023-10-14 10:45:12,863 saving best model |
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2023-10-14 10:45:13,235 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:45:20,499 epoch 2 - iter 144/1445 - loss 0.12655175 - time (sec): 7.26 - samples/sec: 2233.65 - lr: 0.000049 - momentum: 0.000000 |
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2023-10-14 10:45:28,359 epoch 2 - iter 288/1445 - loss 0.11664640 - time (sec): 15.12 - samples/sec: 2234.54 - lr: 0.000049 - momentum: 0.000000 |
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2023-10-14 10:45:35,769 epoch 2 - iter 432/1445 - loss 0.11764083 - time (sec): 22.53 - samples/sec: 2297.07 - lr: 0.000048 - momentum: 0.000000 |
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2023-10-14 10:45:43,380 epoch 2 - iter 576/1445 - loss 0.11288782 - time (sec): 30.14 - samples/sec: 2351.55 - lr: 0.000048 - momentum: 0.000000 |
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2023-10-14 10:45:50,679 epoch 2 - iter 720/1445 - loss 0.11005752 - time (sec): 37.44 - samples/sec: 2372.40 - lr: 0.000047 - momentum: 0.000000 |
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2023-10-14 10:45:57,858 epoch 2 - iter 864/1445 - loss 0.10861039 - time (sec): 44.62 - samples/sec: 2366.36 - lr: 0.000047 - momentum: 0.000000 |
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2023-10-14 10:46:04,905 epoch 2 - iter 1008/1445 - loss 0.11009884 - time (sec): 51.67 - samples/sec: 2363.61 - lr: 0.000046 - momentum: 0.000000 |
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2023-10-14 10:46:12,036 epoch 2 - iter 1152/1445 - loss 0.10756740 - time (sec): 58.80 - samples/sec: 2371.45 - lr: 0.000046 - momentum: 0.000000 |
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2023-10-14 10:46:19,797 epoch 2 - iter 1296/1445 - loss 0.10553537 - time (sec): 66.56 - samples/sec: 2362.48 - lr: 0.000045 - momentum: 0.000000 |
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2023-10-14 10:46:27,342 epoch 2 - iter 1440/1445 - loss 0.10547907 - time (sec): 74.10 - samples/sec: 2370.93 - lr: 0.000044 - momentum: 0.000000 |
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2023-10-14 10:46:27,595 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:46:27,595 EPOCH 2 done: loss 0.1053 - lr: 0.000044 |
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2023-10-14 10:46:31,969 DEV : loss 0.10467828810214996 - f1-score (micro avg) 0.7101 |
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2023-10-14 10:46:31,987 saving best model |
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2023-10-14 10:46:32,513 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:46:40,845 epoch 3 - iter 144/1445 - loss 0.06046434 - time (sec): 8.33 - samples/sec: 2176.51 - lr: 0.000044 - momentum: 0.000000 |
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2023-10-14 10:46:49,225 epoch 3 - iter 288/1445 - loss 0.06004263 - time (sec): 16.71 - samples/sec: 2131.19 - lr: 0.000043 - momentum: 0.000000 |
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2023-10-14 10:46:56,492 epoch 3 - iter 432/1445 - loss 0.06632407 - time (sec): 23.98 - samples/sec: 2165.44 - lr: 0.000043 - momentum: 0.000000 |
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2023-10-14 10:47:03,797 epoch 3 - iter 576/1445 - loss 0.06736150 - time (sec): 31.28 - samples/sec: 2213.57 - lr: 0.000042 - momentum: 0.000000 |
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2023-10-14 10:47:11,200 epoch 3 - iter 720/1445 - loss 0.06752059 - time (sec): 38.68 - samples/sec: 2266.94 - lr: 0.000042 - momentum: 0.000000 |
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2023-10-14 10:47:18,528 epoch 3 - iter 864/1445 - loss 0.07237618 - time (sec): 46.01 - samples/sec: 2285.16 - lr: 0.000041 - momentum: 0.000000 |
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2023-10-14 10:47:26,048 epoch 3 - iter 1008/1445 - loss 0.07408386 - time (sec): 53.53 - samples/sec: 2314.03 - lr: 0.000041 - momentum: 0.000000 |
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2023-10-14 10:47:33,156 epoch 3 - iter 1152/1445 - loss 0.07290332 - time (sec): 60.64 - samples/sec: 2314.08 - lr: 0.000040 - momentum: 0.000000 |
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2023-10-14 10:47:40,398 epoch 3 - iter 1296/1445 - loss 0.07248165 - time (sec): 67.88 - samples/sec: 2319.56 - lr: 0.000039 - momentum: 0.000000 |
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2023-10-14 10:47:47,740 epoch 3 - iter 1440/1445 - loss 0.07325238 - time (sec): 75.22 - samples/sec: 2331.61 - lr: 0.000039 - momentum: 0.000000 |
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2023-10-14 10:47:48,047 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:47:48,048 EPOCH 3 done: loss 0.0730 - lr: 0.000039 |
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2023-10-14 10:47:51,583 DEV : loss 0.09553560614585876 - f1-score (micro avg) 0.8021 |
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2023-10-14 10:47:51,599 saving best model |
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2023-10-14 10:47:52,265 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:47:59,539 epoch 4 - iter 144/1445 - loss 0.04698177 - time (sec): 7.27 - samples/sec: 2415.48 - lr: 0.000038 - momentum: 0.000000 |
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2023-10-14 10:48:07,133 epoch 4 - iter 288/1445 - loss 0.06031754 - time (sec): 14.87 - samples/sec: 2411.66 - lr: 0.000038 - momentum: 0.000000 |
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2023-10-14 10:48:14,165 epoch 4 - iter 432/1445 - loss 0.06263096 - time (sec): 21.90 - samples/sec: 2410.81 - lr: 0.000037 - momentum: 0.000000 |
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2023-10-14 10:48:21,491 epoch 4 - iter 576/1445 - loss 0.05725339 - time (sec): 29.22 - samples/sec: 2417.83 - lr: 0.000037 - momentum: 0.000000 |
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2023-10-14 10:48:28,487 epoch 4 - iter 720/1445 - loss 0.05516418 - time (sec): 36.22 - samples/sec: 2406.40 - lr: 0.000036 - momentum: 0.000000 |
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2023-10-14 10:48:36,217 epoch 4 - iter 864/1445 - loss 0.05343786 - time (sec): 43.95 - samples/sec: 2404.89 - lr: 0.000036 - momentum: 0.000000 |
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2023-10-14 10:48:43,475 epoch 4 - iter 1008/1445 - loss 0.05296204 - time (sec): 51.21 - samples/sec: 2397.09 - lr: 0.000035 - momentum: 0.000000 |
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2023-10-14 10:48:50,864 epoch 4 - iter 1152/1445 - loss 0.05396480 - time (sec): 58.60 - samples/sec: 2397.71 - lr: 0.000034 - momentum: 0.000000 |
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2023-10-14 10:48:58,163 epoch 4 - iter 1296/1445 - loss 0.05465199 - time (sec): 65.90 - samples/sec: 2406.38 - lr: 0.000034 - momentum: 0.000000 |
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2023-10-14 10:49:05,509 epoch 4 - iter 1440/1445 - loss 0.05379926 - time (sec): 73.24 - samples/sec: 2397.56 - lr: 0.000033 - momentum: 0.000000 |
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2023-10-14 10:49:05,752 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:49:05,752 EPOCH 4 done: loss 0.0541 - lr: 0.000033 |
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2023-10-14 10:49:09,309 DEV : loss 0.12118156254291534 - f1-score (micro avg) 0.7946 |
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2023-10-14 10:49:09,326 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:49:16,954 epoch 5 - iter 144/1445 - loss 0.04673101 - time (sec): 7.63 - samples/sec: 2414.26 - lr: 0.000033 - momentum: 0.000000 |
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2023-10-14 10:49:24,004 epoch 5 - iter 288/1445 - loss 0.04488133 - time (sec): 14.68 - samples/sec: 2414.51 - lr: 0.000032 - momentum: 0.000000 |
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2023-10-14 10:49:31,520 epoch 5 - iter 432/1445 - loss 0.04016346 - time (sec): 22.19 - samples/sec: 2439.19 - lr: 0.000032 - momentum: 0.000000 |
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2023-10-14 10:49:38,723 epoch 5 - iter 576/1445 - loss 0.04147102 - time (sec): 29.40 - samples/sec: 2409.52 - lr: 0.000031 - momentum: 0.000000 |
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2023-10-14 10:49:46,016 epoch 5 - iter 720/1445 - loss 0.04117617 - time (sec): 36.69 - samples/sec: 2388.99 - lr: 0.000031 - momentum: 0.000000 |
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2023-10-14 10:49:53,185 epoch 5 - iter 864/1445 - loss 0.04145618 - time (sec): 43.86 - samples/sec: 2366.07 - lr: 0.000030 - momentum: 0.000000 |
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2023-10-14 10:50:00,848 epoch 5 - iter 1008/1445 - loss 0.03979828 - time (sec): 51.52 - samples/sec: 2367.21 - lr: 0.000029 - momentum: 0.000000 |
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2023-10-14 10:50:08,189 epoch 5 - iter 1152/1445 - loss 0.03982370 - time (sec): 58.86 - samples/sec: 2374.01 - lr: 0.000029 - momentum: 0.000000 |
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2023-10-14 10:50:15,584 epoch 5 - iter 1296/1445 - loss 0.04077806 - time (sec): 66.26 - samples/sec: 2388.64 - lr: 0.000028 - momentum: 0.000000 |
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2023-10-14 10:50:23,148 epoch 5 - iter 1440/1445 - loss 0.03927038 - time (sec): 73.82 - samples/sec: 2380.09 - lr: 0.000028 - momentum: 0.000000 |
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2023-10-14 10:50:23,369 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:50:23,369 EPOCH 5 done: loss 0.0393 - lr: 0.000028 |
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2023-10-14 10:50:27,269 DEV : loss 0.15388108789920807 - f1-score (micro avg) 0.7917 |
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2023-10-14 10:50:27,287 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:50:34,633 epoch 6 - iter 144/1445 - loss 0.03233428 - time (sec): 7.34 - samples/sec: 2362.50 - lr: 0.000027 - momentum: 0.000000 |
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2023-10-14 10:50:41,959 epoch 6 - iter 288/1445 - loss 0.03501451 - time (sec): 14.67 - samples/sec: 2390.85 - lr: 0.000027 - momentum: 0.000000 |
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2023-10-14 10:50:49,055 epoch 6 - iter 432/1445 - loss 0.03123834 - time (sec): 21.77 - samples/sec: 2411.58 - lr: 0.000026 - momentum: 0.000000 |
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2023-10-14 10:50:56,443 epoch 6 - iter 576/1445 - loss 0.03274913 - time (sec): 29.16 - samples/sec: 2419.30 - lr: 0.000026 - momentum: 0.000000 |
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2023-10-14 10:51:03,609 epoch 6 - iter 720/1445 - loss 0.03314690 - time (sec): 36.32 - samples/sec: 2406.97 - lr: 0.000025 - momentum: 0.000000 |
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2023-10-14 10:51:10,863 epoch 6 - iter 864/1445 - loss 0.03210885 - time (sec): 43.58 - samples/sec: 2410.60 - lr: 0.000024 - momentum: 0.000000 |
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2023-10-14 10:51:18,264 epoch 6 - iter 1008/1445 - loss 0.03115240 - time (sec): 50.98 - samples/sec: 2410.40 - lr: 0.000024 - momentum: 0.000000 |
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2023-10-14 10:51:25,820 epoch 6 - iter 1152/1445 - loss 0.03008407 - time (sec): 58.53 - samples/sec: 2430.27 - lr: 0.000023 - momentum: 0.000000 |
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2023-10-14 10:51:32,892 epoch 6 - iter 1296/1445 - loss 0.03095943 - time (sec): 65.60 - samples/sec: 2425.45 - lr: 0.000023 - momentum: 0.000000 |
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2023-10-14 10:51:39,991 epoch 6 - iter 1440/1445 - loss 0.03162133 - time (sec): 72.70 - samples/sec: 2417.44 - lr: 0.000022 - momentum: 0.000000 |
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2023-10-14 10:51:40,215 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:51:40,215 EPOCH 6 done: loss 0.0317 - lr: 0.000022 |
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2023-10-14 10:51:43,805 DEV : loss 0.19756034016609192 - f1-score (micro avg) 0.8016 |
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2023-10-14 10:51:43,821 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:51:51,088 epoch 7 - iter 144/1445 - loss 0.01816229 - time (sec): 7.27 - samples/sec: 2414.93 - lr: 0.000022 - momentum: 0.000000 |
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2023-10-14 10:51:58,649 epoch 7 - iter 288/1445 - loss 0.01954064 - time (sec): 14.83 - samples/sec: 2471.92 - lr: 0.000021 - momentum: 0.000000 |
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2023-10-14 10:52:05,759 epoch 7 - iter 432/1445 - loss 0.01867134 - time (sec): 21.94 - samples/sec: 2439.90 - lr: 0.000021 - momentum: 0.000000 |
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2023-10-14 10:52:13,556 epoch 7 - iter 576/1445 - loss 0.01895690 - time (sec): 29.73 - samples/sec: 2418.92 - lr: 0.000020 - momentum: 0.000000 |
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2023-10-14 10:52:20,679 epoch 7 - iter 720/1445 - loss 0.01836345 - time (sec): 36.86 - samples/sec: 2400.83 - lr: 0.000019 - momentum: 0.000000 |
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2023-10-14 10:52:27,667 epoch 7 - iter 864/1445 - loss 0.01877869 - time (sec): 43.84 - samples/sec: 2396.78 - lr: 0.000019 - momentum: 0.000000 |
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2023-10-14 10:52:35,009 epoch 7 - iter 1008/1445 - loss 0.02080686 - time (sec): 51.19 - samples/sec: 2419.50 - lr: 0.000018 - momentum: 0.000000 |
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2023-10-14 10:52:42,373 epoch 7 - iter 1152/1445 - loss 0.02134693 - time (sec): 58.55 - samples/sec: 2423.15 - lr: 0.000018 - momentum: 0.000000 |
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2023-10-14 10:52:49,576 epoch 7 - iter 1296/1445 - loss 0.02105516 - time (sec): 65.75 - samples/sec: 2420.11 - lr: 0.000017 - momentum: 0.000000 |
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2023-10-14 10:52:56,887 epoch 7 - iter 1440/1445 - loss 0.02073299 - time (sec): 73.06 - samples/sec: 2406.17 - lr: 0.000017 - momentum: 0.000000 |
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2023-10-14 10:52:57,114 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:52:57,115 EPOCH 7 done: loss 0.0209 - lr: 0.000017 |
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2023-10-14 10:53:00,712 DEV : loss 0.18008936941623688 - f1-score (micro avg) 0.8011 |
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2023-10-14 10:53:00,729 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:53:07,996 epoch 8 - iter 144/1445 - loss 0.01866497 - time (sec): 7.27 - samples/sec: 2300.59 - lr: 0.000016 - momentum: 0.000000 |
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2023-10-14 10:53:15,313 epoch 8 - iter 288/1445 - loss 0.01466923 - time (sec): 14.58 - samples/sec: 2372.09 - lr: 0.000016 - momentum: 0.000000 |
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2023-10-14 10:53:22,675 epoch 8 - iter 432/1445 - loss 0.01583407 - time (sec): 21.95 - samples/sec: 2384.78 - lr: 0.000015 - momentum: 0.000000 |
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2023-10-14 10:53:29,992 epoch 8 - iter 576/1445 - loss 0.01493921 - time (sec): 29.26 - samples/sec: 2381.30 - lr: 0.000014 - momentum: 0.000000 |
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2023-10-14 10:53:37,264 epoch 8 - iter 720/1445 - loss 0.01503871 - time (sec): 36.53 - samples/sec: 2407.26 - lr: 0.000014 - momentum: 0.000000 |
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2023-10-14 10:53:44,308 epoch 8 - iter 864/1445 - loss 0.01515293 - time (sec): 43.58 - samples/sec: 2399.36 - lr: 0.000013 - momentum: 0.000000 |
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2023-10-14 10:53:51,766 epoch 8 - iter 1008/1445 - loss 0.01576861 - time (sec): 51.04 - samples/sec: 2404.97 - lr: 0.000013 - momentum: 0.000000 |
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2023-10-14 10:53:59,034 epoch 8 - iter 1152/1445 - loss 0.01561594 - time (sec): 58.30 - samples/sec: 2408.13 - lr: 0.000012 - momentum: 0.000000 |
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2023-10-14 10:54:06,080 epoch 8 - iter 1296/1445 - loss 0.01534350 - time (sec): 65.35 - samples/sec: 2411.17 - lr: 0.000012 - momentum: 0.000000 |
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2023-10-14 10:54:13,533 epoch 8 - iter 1440/1445 - loss 0.01509812 - time (sec): 72.80 - samples/sec: 2409.56 - lr: 0.000011 - momentum: 0.000000 |
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2023-10-14 10:54:13,784 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:54:13,784 EPOCH 8 done: loss 0.0151 - lr: 0.000011 |
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2023-10-14 10:54:17,824 DEV : loss 0.20430612564086914 - f1-score (micro avg) 0.7978 |
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2023-10-14 10:54:17,841 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:54:25,386 epoch 9 - iter 144/1445 - loss 0.01055124 - time (sec): 7.54 - samples/sec: 2408.34 - lr: 0.000011 - momentum: 0.000000 |
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2023-10-14 10:54:32,660 epoch 9 - iter 288/1445 - loss 0.00857411 - time (sec): 14.82 - samples/sec: 2384.81 - lr: 0.000010 - momentum: 0.000000 |
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2023-10-14 10:54:39,915 epoch 9 - iter 432/1445 - loss 0.00889903 - time (sec): 22.07 - samples/sec: 2361.30 - lr: 0.000009 - momentum: 0.000000 |
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2023-10-14 10:54:47,643 epoch 9 - iter 576/1445 - loss 0.01030940 - time (sec): 29.80 - samples/sec: 2394.86 - lr: 0.000009 - momentum: 0.000000 |
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2023-10-14 10:54:54,820 epoch 9 - iter 720/1445 - loss 0.00993058 - time (sec): 36.98 - samples/sec: 2400.63 - lr: 0.000008 - momentum: 0.000000 |
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2023-10-14 10:55:02,175 epoch 9 - iter 864/1445 - loss 0.00936448 - time (sec): 44.33 - samples/sec: 2406.24 - lr: 0.000008 - momentum: 0.000000 |
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2023-10-14 10:55:09,201 epoch 9 - iter 1008/1445 - loss 0.00913328 - time (sec): 51.36 - samples/sec: 2404.99 - lr: 0.000007 - momentum: 0.000000 |
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2023-10-14 10:55:16,575 epoch 9 - iter 1152/1445 - loss 0.00941487 - time (sec): 58.73 - samples/sec: 2408.84 - lr: 0.000007 - momentum: 0.000000 |
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2023-10-14 10:55:23,825 epoch 9 - iter 1296/1445 - loss 0.01026341 - time (sec): 65.98 - samples/sec: 2401.83 - lr: 0.000006 - momentum: 0.000000 |
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2023-10-14 10:55:31,036 epoch 9 - iter 1440/1445 - loss 0.01047293 - time (sec): 73.19 - samples/sec: 2400.81 - lr: 0.000006 - momentum: 0.000000 |
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2023-10-14 10:55:31,280 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:55:31,280 EPOCH 9 done: loss 0.0105 - lr: 0.000006 |
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2023-10-14 10:55:34,878 DEV : loss 0.1839500218629837 - f1-score (micro avg) 0.7974 |
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2023-10-14 10:55:34,896 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:55:42,196 epoch 10 - iter 144/1445 - loss 0.00490526 - time (sec): 7.30 - samples/sec: 2287.22 - lr: 0.000005 - momentum: 0.000000 |
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2023-10-14 10:55:49,779 epoch 10 - iter 288/1445 - loss 0.00524218 - time (sec): 14.88 - samples/sec: 2333.86 - lr: 0.000004 - momentum: 0.000000 |
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2023-10-14 10:55:57,744 epoch 10 - iter 432/1445 - loss 0.00648842 - time (sec): 22.85 - samples/sec: 2293.26 - lr: 0.000004 - momentum: 0.000000 |
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2023-10-14 10:56:05,487 epoch 10 - iter 576/1445 - loss 0.00656819 - time (sec): 30.59 - samples/sec: 2325.72 - lr: 0.000003 - momentum: 0.000000 |
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2023-10-14 10:56:12,959 epoch 10 - iter 720/1445 - loss 0.00698945 - time (sec): 38.06 - samples/sec: 2354.45 - lr: 0.000003 - momentum: 0.000000 |
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2023-10-14 10:56:20,142 epoch 10 - iter 864/1445 - loss 0.00778598 - time (sec): 45.24 - samples/sec: 2362.14 - lr: 0.000002 - momentum: 0.000000 |
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2023-10-14 10:56:27,101 epoch 10 - iter 1008/1445 - loss 0.00737225 - time (sec): 52.20 - samples/sec: 2348.21 - lr: 0.000002 - momentum: 0.000000 |
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2023-10-14 10:56:34,107 epoch 10 - iter 1152/1445 - loss 0.00697948 - time (sec): 59.21 - samples/sec: 2352.75 - lr: 0.000001 - momentum: 0.000000 |
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2023-10-14 10:56:41,417 epoch 10 - iter 1296/1445 - loss 0.00700128 - time (sec): 66.52 - samples/sec: 2371.69 - lr: 0.000001 - momentum: 0.000000 |
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2023-10-14 10:56:48,753 epoch 10 - iter 1440/1445 - loss 0.00696742 - time (sec): 73.86 - samples/sec: 2376.15 - lr: 0.000000 - momentum: 0.000000 |
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2023-10-14 10:56:49,020 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:56:49,021 EPOCH 10 done: loss 0.0070 - lr: 0.000000 |
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2023-10-14 10:56:52,539 DEV : loss 0.19384992122650146 - f1-score (micro avg) 0.8093 |
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2023-10-14 10:56:52,555 saving best model |
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2023-10-14 10:56:53,410 ---------------------------------------------------------------------------------------------------- |
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2023-10-14 10:56:53,411 Loading model from best epoch ... |
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2023-10-14 10:56:55,129 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 |
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2023-10-14 10:56:58,276 |
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Results: |
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- F-score (micro) 0.7959 |
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- F-score (macro) 0.6975 |
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- Accuracy 0.6749 |
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By class: |
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precision recall f1-score support |
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PER 0.8184 0.7759 0.7966 482 |
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LOC 0.8949 0.7991 0.8443 458 |
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ORG 0.5091 0.4058 0.4516 69 |
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micro avg 0.8339 0.7611 0.7959 1009 |
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macro avg 0.7408 0.6603 0.6975 1009 |
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weighted avg 0.8319 0.7611 0.7947 1009 |
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2023-10-14 10:56:58,276 ---------------------------------------------------------------------------------------------------- |
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