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2023-10-25 13:04:00,403 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:04:00,403 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(64001, 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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2023-10-25 13:04:00,404 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:04:00,404 MultiCorpus: 6183 train + 680 dev + 2113 test sentences |
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- NER_HIPE_2022 Corpus: 6183 train + 680 dev + 2113 test sentences - /root/.flair/datasets/ner_hipe_2022/v2.1/topres19th/en/with_doc_seperator |
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2023-10-25 13:04:00,404 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:04:00,404 Train: 6183 sentences |
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2023-10-25 13:04:00,404 (train_with_dev=False, train_with_test=False) |
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2023-10-25 13:04:00,404 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:04:00,404 Training Params: |
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2023-10-25 13:04:00,404 - learning_rate: "5e-05" |
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2023-10-25 13:04:00,404 - mini_batch_size: "8" |
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2023-10-25 13:04:00,404 - max_epochs: "10" |
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2023-10-25 13:04:00,404 - shuffle: "True" |
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2023-10-25 13:04:00,404 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:04:00,404 Plugins: |
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2023-10-25 13:04:00,404 - TensorboardLogger |
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2023-10-25 13:04:00,404 - LinearScheduler | warmup_fraction: '0.1' |
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2023-10-25 13:04:00,404 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:04:00,404 Final evaluation on model from best epoch (best-model.pt) |
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2023-10-25 13:04:00,405 - metric: "('micro avg', 'f1-score')" |
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2023-10-25 13:04:00,405 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:04:00,405 Computation: |
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2023-10-25 13:04:00,405 - compute on device: cuda:0 |
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2023-10-25 13:04:00,405 - embedding storage: none |
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2023-10-25 13:04:00,405 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:04:00,405 Model training base path: "hmbench-topres19th/en-dbmdz/bert-base-historic-multilingual-64k-td-cased-bs8-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-5" |
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2023-10-25 13:04:00,405 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:04:00,405 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:04:00,405 Logging anything other than scalars to TensorBoard is currently not supported. |
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2023-10-25 13:04:04,871 epoch 1 - iter 77/773 - loss 1.62607859 - time (sec): 4.47 - samples/sec: 2919.55 - lr: 0.000005 - momentum: 0.000000 |
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2023-10-25 13:04:09,448 epoch 1 - iter 154/773 - loss 0.94210245 - time (sec): 9.04 - samples/sec: 2835.22 - lr: 0.000010 - momentum: 0.000000 |
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2023-10-25 13:04:14,272 epoch 1 - iter 231/773 - loss 0.69033315 - time (sec): 13.87 - samples/sec: 2712.58 - lr: 0.000015 - momentum: 0.000000 |
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2023-10-25 13:04:19,189 epoch 1 - iter 308/773 - loss 0.55795676 - time (sec): 18.78 - samples/sec: 2638.02 - lr: 0.000020 - momentum: 0.000000 |
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2023-10-25 13:04:23,842 epoch 1 - iter 385/773 - loss 0.47173138 - time (sec): 23.44 - samples/sec: 2617.54 - lr: 0.000025 - momentum: 0.000000 |
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2023-10-25 13:04:28,472 epoch 1 - iter 462/773 - loss 0.41386971 - time (sec): 28.07 - samples/sec: 2627.27 - lr: 0.000030 - momentum: 0.000000 |
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2023-10-25 13:04:32,979 epoch 1 - iter 539/773 - loss 0.37054284 - time (sec): 32.57 - samples/sec: 2625.88 - lr: 0.000035 - momentum: 0.000000 |
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2023-10-25 13:04:37,466 epoch 1 - iter 616/773 - loss 0.33663528 - time (sec): 37.06 - samples/sec: 2642.50 - lr: 0.000040 - momentum: 0.000000 |
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2023-10-25 13:04:41,752 epoch 1 - iter 693/773 - loss 0.30816500 - time (sec): 41.35 - samples/sec: 2678.58 - lr: 0.000045 - momentum: 0.000000 |
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2023-10-25 13:04:46,095 epoch 1 - iter 770/773 - loss 0.28446225 - time (sec): 45.69 - samples/sec: 2712.76 - lr: 0.000050 - momentum: 0.000000 |
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2023-10-25 13:04:46,249 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:04:46,249 EPOCH 1 done: loss 0.2838 - lr: 0.000050 |
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2023-10-25 13:04:49,502 DEV : loss 0.05165766924619675 - f1-score (micro avg) 0.7323 |
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2023-10-25 13:04:49,522 saving best model |
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2023-10-25 13:04:50,070 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:04:54,732 epoch 2 - iter 77/773 - loss 0.10202012 - time (sec): 4.66 - samples/sec: 2459.39 - lr: 0.000049 - momentum: 0.000000 |
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2023-10-25 13:04:59,242 epoch 2 - iter 154/773 - loss 0.08419062 - time (sec): 9.17 - samples/sec: 2528.27 - lr: 0.000049 - momentum: 0.000000 |
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2023-10-25 13:05:03,731 epoch 2 - iter 231/773 - loss 0.08259793 - time (sec): 13.66 - samples/sec: 2568.79 - lr: 0.000048 - momentum: 0.000000 |
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2023-10-25 13:05:08,253 epoch 2 - iter 308/773 - loss 0.08289606 - time (sec): 18.18 - samples/sec: 2638.40 - lr: 0.000048 - momentum: 0.000000 |
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2023-10-25 13:05:12,813 epoch 2 - iter 385/773 - loss 0.08040769 - time (sec): 22.74 - samples/sec: 2694.06 - lr: 0.000047 - momentum: 0.000000 |
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2023-10-25 13:05:17,136 epoch 2 - iter 462/773 - loss 0.07924733 - time (sec): 27.06 - samples/sec: 2716.80 - lr: 0.000047 - momentum: 0.000000 |
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2023-10-25 13:05:21,425 epoch 2 - iter 539/773 - loss 0.07828472 - time (sec): 31.35 - samples/sec: 2778.47 - lr: 0.000046 - momentum: 0.000000 |
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2023-10-25 13:05:25,710 epoch 2 - iter 616/773 - loss 0.07838880 - time (sec): 35.64 - samples/sec: 2786.75 - lr: 0.000046 - momentum: 0.000000 |
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2023-10-25 13:05:29,957 epoch 2 - iter 693/773 - loss 0.07907713 - time (sec): 39.89 - samples/sec: 2791.31 - lr: 0.000045 - momentum: 0.000000 |
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2023-10-25 13:05:34,285 epoch 2 - iter 770/773 - loss 0.07672251 - time (sec): 44.21 - samples/sec: 2801.22 - lr: 0.000044 - momentum: 0.000000 |
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2023-10-25 13:05:34,454 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:05:34,455 EPOCH 2 done: loss 0.0767 - lr: 0.000044 |
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2023-10-25 13:05:37,402 DEV : loss 0.05662866681814194 - f1-score (micro avg) 0.7628 |
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2023-10-25 13:05:37,419 saving best model |
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2023-10-25 13:05:38,170 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:05:43,368 epoch 3 - iter 77/773 - loss 0.04830238 - time (sec): 5.19 - samples/sec: 2322.43 - lr: 0.000044 - momentum: 0.000000 |
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2023-10-25 13:05:47,869 epoch 3 - iter 154/773 - loss 0.05073064 - time (sec): 9.70 - samples/sec: 2497.06 - lr: 0.000043 - momentum: 0.000000 |
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2023-10-25 13:05:52,586 epoch 3 - iter 231/773 - loss 0.05345361 - time (sec): 14.41 - samples/sec: 2634.94 - lr: 0.000043 - momentum: 0.000000 |
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2023-10-25 13:05:57,105 epoch 3 - iter 308/773 - loss 0.05233532 - time (sec): 18.93 - samples/sec: 2619.65 - lr: 0.000042 - momentum: 0.000000 |
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2023-10-25 13:06:01,765 epoch 3 - iter 385/773 - loss 0.05274950 - time (sec): 23.59 - samples/sec: 2627.87 - lr: 0.000042 - momentum: 0.000000 |
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2023-10-25 13:06:06,320 epoch 3 - iter 462/773 - loss 0.05328798 - time (sec): 28.15 - samples/sec: 2619.52 - lr: 0.000041 - momentum: 0.000000 |
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2023-10-25 13:06:10,830 epoch 3 - iter 539/773 - loss 0.05175706 - time (sec): 32.66 - samples/sec: 2640.92 - lr: 0.000041 - momentum: 0.000000 |
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2023-10-25 13:06:15,426 epoch 3 - iter 616/773 - loss 0.05144252 - time (sec): 37.25 - samples/sec: 2655.35 - lr: 0.000040 - momentum: 0.000000 |
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2023-10-25 13:06:20,100 epoch 3 - iter 693/773 - loss 0.05097205 - time (sec): 41.93 - samples/sec: 2651.47 - lr: 0.000039 - momentum: 0.000000 |
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2023-10-25 13:06:24,629 epoch 3 - iter 770/773 - loss 0.05141460 - time (sec): 46.46 - samples/sec: 2667.56 - lr: 0.000039 - momentum: 0.000000 |
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2023-10-25 13:06:24,796 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:06:24,797 EPOCH 3 done: loss 0.0514 - lr: 0.000039 |
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2023-10-25 13:06:27,708 DEV : loss 0.08030106127262115 - f1-score (micro avg) 0.7182 |
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2023-10-25 13:06:27,729 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:06:32,291 epoch 4 - iter 77/773 - loss 0.03816760 - time (sec): 4.56 - samples/sec: 2653.55 - lr: 0.000038 - momentum: 0.000000 |
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2023-10-25 13:06:37,003 epoch 4 - iter 154/773 - loss 0.03377926 - time (sec): 9.27 - samples/sec: 2620.46 - lr: 0.000038 - momentum: 0.000000 |
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2023-10-25 13:06:41,801 epoch 4 - iter 231/773 - loss 0.03420877 - time (sec): 14.07 - samples/sec: 2623.09 - lr: 0.000037 - momentum: 0.000000 |
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2023-10-25 13:06:46,421 epoch 4 - iter 308/773 - loss 0.03420744 - time (sec): 18.69 - samples/sec: 2623.52 - lr: 0.000037 - momentum: 0.000000 |
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2023-10-25 13:06:50,969 epoch 4 - iter 385/773 - loss 0.03441451 - time (sec): 23.24 - samples/sec: 2597.91 - lr: 0.000036 - momentum: 0.000000 |
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2023-10-25 13:06:55,487 epoch 4 - iter 462/773 - loss 0.03487924 - time (sec): 27.76 - samples/sec: 2589.27 - lr: 0.000036 - momentum: 0.000000 |
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2023-10-25 13:07:00,136 epoch 4 - iter 539/773 - loss 0.03545083 - time (sec): 32.41 - samples/sec: 2615.60 - lr: 0.000035 - momentum: 0.000000 |
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2023-10-25 13:07:04,532 epoch 4 - iter 616/773 - loss 0.03574374 - time (sec): 36.80 - samples/sec: 2654.64 - lr: 0.000034 - momentum: 0.000000 |
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2023-10-25 13:07:09,155 epoch 4 - iter 693/773 - loss 0.03593766 - time (sec): 41.42 - samples/sec: 2684.99 - lr: 0.000034 - momentum: 0.000000 |
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2023-10-25 13:07:13,897 epoch 4 - iter 770/773 - loss 0.03530953 - time (sec): 46.17 - samples/sec: 2684.07 - lr: 0.000033 - momentum: 0.000000 |
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2023-10-25 13:07:14,074 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:07:14,075 EPOCH 4 done: loss 0.0354 - lr: 0.000033 |
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2023-10-25 13:07:16,611 DEV : loss 0.08339047431945801 - f1-score (micro avg) 0.7649 |
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2023-10-25 13:07:16,630 saving best model |
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2023-10-25 13:07:17,281 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:07:22,250 epoch 5 - iter 77/773 - loss 0.01949160 - time (sec): 4.97 - samples/sec: 2636.17 - lr: 0.000033 - momentum: 0.000000 |
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2023-10-25 13:07:27,068 epoch 5 - iter 154/773 - loss 0.01928080 - time (sec): 9.78 - samples/sec: 2553.53 - lr: 0.000032 - momentum: 0.000000 |
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2023-10-25 13:07:31,973 epoch 5 - iter 231/773 - loss 0.02144756 - time (sec): 14.69 - samples/sec: 2503.66 - lr: 0.000032 - momentum: 0.000000 |
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2023-10-25 13:07:36,776 epoch 5 - iter 308/773 - loss 0.02257405 - time (sec): 19.49 - samples/sec: 2478.57 - lr: 0.000031 - momentum: 0.000000 |
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2023-10-25 13:07:41,608 epoch 5 - iter 385/773 - loss 0.02362110 - time (sec): 24.32 - samples/sec: 2520.77 - lr: 0.000031 - momentum: 0.000000 |
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2023-10-25 13:07:46,203 epoch 5 - iter 462/773 - loss 0.02401721 - time (sec): 28.92 - samples/sec: 2518.69 - lr: 0.000030 - momentum: 0.000000 |
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2023-10-25 13:07:50,848 epoch 5 - iter 539/773 - loss 0.02564729 - time (sec): 33.56 - samples/sec: 2527.50 - lr: 0.000029 - momentum: 0.000000 |
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2023-10-25 13:07:55,431 epoch 5 - iter 616/773 - loss 0.02576209 - time (sec): 38.15 - samples/sec: 2572.76 - lr: 0.000029 - momentum: 0.000000 |
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2023-10-25 13:07:59,836 epoch 5 - iter 693/773 - loss 0.02549268 - time (sec): 42.55 - samples/sec: 2611.03 - lr: 0.000028 - momentum: 0.000000 |
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2023-10-25 13:08:04,104 epoch 5 - iter 770/773 - loss 0.02500032 - time (sec): 46.82 - samples/sec: 2646.22 - lr: 0.000028 - momentum: 0.000000 |
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2023-10-25 13:08:04,263 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:08:04,263 EPOCH 5 done: loss 0.0250 - lr: 0.000028 |
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2023-10-25 13:08:06,931 DEV : loss 0.10233461856842041 - f1-score (micro avg) 0.7579 |
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2023-10-25 13:08:06,952 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:08:11,484 epoch 6 - iter 77/773 - loss 0.02403484 - time (sec): 4.53 - samples/sec: 2724.96 - lr: 0.000027 - momentum: 0.000000 |
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2023-10-25 13:08:16,103 epoch 6 - iter 154/773 - loss 0.01933766 - time (sec): 9.15 - samples/sec: 2749.34 - lr: 0.000027 - momentum: 0.000000 |
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2023-10-25 13:08:20,644 epoch 6 - iter 231/773 - loss 0.01675474 - time (sec): 13.69 - samples/sec: 2703.76 - lr: 0.000026 - momentum: 0.000000 |
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2023-10-25 13:08:25,139 epoch 6 - iter 308/773 - loss 0.01770050 - time (sec): 18.18 - samples/sec: 2730.90 - lr: 0.000026 - momentum: 0.000000 |
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2023-10-25 13:08:29,794 epoch 6 - iter 385/773 - loss 0.01697379 - time (sec): 22.84 - samples/sec: 2721.83 - lr: 0.000025 - momentum: 0.000000 |
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2023-10-25 13:08:34,492 epoch 6 - iter 462/773 - loss 0.01647189 - time (sec): 27.54 - samples/sec: 2720.32 - lr: 0.000024 - momentum: 0.000000 |
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2023-10-25 13:08:39,812 epoch 6 - iter 539/773 - loss 0.01695804 - time (sec): 32.86 - samples/sec: 2653.54 - lr: 0.000024 - momentum: 0.000000 |
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2023-10-25 13:08:44,380 epoch 6 - iter 616/773 - loss 0.01663896 - time (sec): 37.43 - samples/sec: 2653.24 - lr: 0.000023 - momentum: 0.000000 |
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2023-10-25 13:08:48,904 epoch 6 - iter 693/773 - loss 0.01722230 - time (sec): 41.95 - samples/sec: 2662.44 - lr: 0.000023 - momentum: 0.000000 |
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2023-10-25 13:08:53,262 epoch 6 - iter 770/773 - loss 0.01642065 - time (sec): 46.31 - samples/sec: 2675.35 - lr: 0.000022 - momentum: 0.000000 |
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2023-10-25 13:08:53,417 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:08:53,417 EPOCH 6 done: loss 0.0164 - lr: 0.000022 |
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2023-10-25 13:08:56,297 DEV : loss 0.10584240406751633 - f1-score (micro avg) 0.7992 |
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2023-10-25 13:08:56,320 saving best model |
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2023-10-25 13:08:56,974 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:09:01,620 epoch 7 - iter 77/773 - loss 0.01534673 - time (sec): 4.64 - samples/sec: 2796.75 - lr: 0.000022 - momentum: 0.000000 |
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2023-10-25 13:09:06,285 epoch 7 - iter 154/773 - loss 0.01242129 - time (sec): 9.31 - samples/sec: 2688.82 - lr: 0.000021 - momentum: 0.000000 |
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2023-10-25 13:09:11,077 epoch 7 - iter 231/773 - loss 0.01054806 - time (sec): 14.10 - samples/sec: 2681.47 - lr: 0.000021 - momentum: 0.000000 |
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2023-10-25 13:09:15,836 epoch 7 - iter 308/773 - loss 0.01064088 - time (sec): 18.86 - samples/sec: 2673.72 - lr: 0.000020 - momentum: 0.000000 |
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2023-10-25 13:09:20,462 epoch 7 - iter 385/773 - loss 0.01089602 - time (sec): 23.48 - samples/sec: 2643.79 - lr: 0.000019 - momentum: 0.000000 |
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2023-10-25 13:09:25,076 epoch 7 - iter 462/773 - loss 0.01071434 - time (sec): 28.10 - samples/sec: 2651.83 - lr: 0.000019 - momentum: 0.000000 |
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2023-10-25 13:09:29,777 epoch 7 - iter 539/773 - loss 0.01088053 - time (sec): 32.80 - samples/sec: 2648.61 - lr: 0.000018 - momentum: 0.000000 |
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2023-10-25 13:09:34,667 epoch 7 - iter 616/773 - loss 0.01092188 - time (sec): 37.69 - samples/sec: 2627.23 - lr: 0.000018 - momentum: 0.000000 |
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2023-10-25 13:09:39,693 epoch 7 - iter 693/773 - loss 0.01146992 - time (sec): 42.72 - samples/sec: 2633.32 - lr: 0.000017 - momentum: 0.000000 |
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2023-10-25 13:09:44,498 epoch 7 - iter 770/773 - loss 0.01173852 - time (sec): 47.52 - samples/sec: 2608.77 - lr: 0.000017 - momentum: 0.000000 |
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2023-10-25 13:09:44,678 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:09:44,678 EPOCH 7 done: loss 0.0117 - lr: 0.000017 |
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2023-10-25 13:09:47,214 DEV : loss 0.11367938667535782 - f1-score (micro avg) 0.7702 |
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2023-10-25 13:09:47,233 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:09:52,081 epoch 8 - iter 77/773 - loss 0.00915681 - time (sec): 4.85 - samples/sec: 2566.64 - lr: 0.000016 - momentum: 0.000000 |
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2023-10-25 13:09:56,977 epoch 8 - iter 154/773 - loss 0.00927730 - time (sec): 9.74 - samples/sec: 2495.94 - lr: 0.000016 - momentum: 0.000000 |
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2023-10-25 13:10:01,947 epoch 8 - iter 231/773 - loss 0.00889633 - time (sec): 14.71 - samples/sec: 2492.37 - lr: 0.000015 - momentum: 0.000000 |
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2023-10-25 13:10:06,837 epoch 8 - iter 308/773 - loss 0.00755093 - time (sec): 19.60 - samples/sec: 2506.99 - lr: 0.000014 - momentum: 0.000000 |
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2023-10-25 13:10:11,651 epoch 8 - iter 385/773 - loss 0.00800710 - time (sec): 24.42 - samples/sec: 2523.49 - lr: 0.000014 - momentum: 0.000000 |
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2023-10-25 13:10:16,478 epoch 8 - iter 462/773 - loss 0.00799662 - time (sec): 29.24 - samples/sec: 2517.18 - lr: 0.000013 - momentum: 0.000000 |
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2023-10-25 13:10:21,349 epoch 8 - iter 539/773 - loss 0.00766083 - time (sec): 34.11 - samples/sec: 2569.14 - lr: 0.000013 - momentum: 0.000000 |
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2023-10-25 13:10:26,302 epoch 8 - iter 616/773 - loss 0.00763491 - time (sec): 39.07 - samples/sec: 2560.31 - lr: 0.000012 - momentum: 0.000000 |
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2023-10-25 13:10:31,080 epoch 8 - iter 693/773 - loss 0.00766449 - time (sec): 43.84 - samples/sec: 2546.17 - lr: 0.000012 - momentum: 0.000000 |
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2023-10-25 13:10:35,826 epoch 8 - iter 770/773 - loss 0.00742265 - time (sec): 48.59 - samples/sec: 2547.19 - lr: 0.000011 - momentum: 0.000000 |
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2023-10-25 13:10:36,008 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:10:36,009 EPOCH 8 done: loss 0.0075 - lr: 0.000011 |
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2023-10-25 13:10:38,904 DEV : loss 0.1300455778837204 - f1-score (micro avg) 0.755 |
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2023-10-25 13:10:38,923 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:10:43,606 epoch 9 - iter 77/773 - loss 0.00575536 - time (sec): 4.68 - samples/sec: 2808.71 - lr: 0.000011 - momentum: 0.000000 |
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2023-10-25 13:10:48,290 epoch 9 - iter 154/773 - loss 0.00667575 - time (sec): 9.37 - samples/sec: 2659.97 - lr: 0.000010 - momentum: 0.000000 |
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2023-10-25 13:10:52,840 epoch 9 - iter 231/773 - loss 0.00556811 - time (sec): 13.92 - samples/sec: 2714.47 - lr: 0.000009 - momentum: 0.000000 |
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2023-10-25 13:10:57,278 epoch 9 - iter 308/773 - loss 0.00712098 - time (sec): 18.35 - samples/sec: 2701.17 - lr: 0.000009 - momentum: 0.000000 |
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2023-10-25 13:11:01,945 epoch 9 - iter 385/773 - loss 0.00671541 - time (sec): 23.02 - samples/sec: 2693.66 - lr: 0.000008 - momentum: 0.000000 |
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2023-10-25 13:11:06,517 epoch 9 - iter 462/773 - loss 0.00677819 - time (sec): 27.59 - samples/sec: 2706.24 - lr: 0.000008 - momentum: 0.000000 |
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2023-10-25 13:11:11,088 epoch 9 - iter 539/773 - loss 0.00647608 - time (sec): 32.16 - samples/sec: 2718.72 - lr: 0.000007 - momentum: 0.000000 |
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2023-10-25 13:11:15,685 epoch 9 - iter 616/773 - loss 0.00626968 - time (sec): 36.76 - samples/sec: 2728.56 - lr: 0.000007 - momentum: 0.000000 |
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2023-10-25 13:11:20,159 epoch 9 - iter 693/773 - loss 0.00611977 - time (sec): 41.23 - samples/sec: 2725.48 - lr: 0.000006 - momentum: 0.000000 |
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2023-10-25 13:11:24,583 epoch 9 - iter 770/773 - loss 0.00625835 - time (sec): 45.66 - samples/sec: 2715.43 - lr: 0.000006 - momentum: 0.000000 |
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2023-10-25 13:11:24,746 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:11:24,747 EPOCH 9 done: loss 0.0062 - lr: 0.000006 |
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2023-10-25 13:11:27,348 DEV : loss 0.13065063953399658 - f1-score (micro avg) 0.7686 |
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2023-10-25 13:11:27,366 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:11:32,017 epoch 10 - iter 77/773 - loss 0.00367421 - time (sec): 4.65 - samples/sec: 2585.53 - lr: 0.000005 - momentum: 0.000000 |
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2023-10-25 13:11:37,336 epoch 10 - iter 154/773 - loss 0.00561623 - time (sec): 9.97 - samples/sec: 2487.55 - lr: 0.000005 - momentum: 0.000000 |
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2023-10-25 13:11:41,777 epoch 10 - iter 231/773 - loss 0.00497335 - time (sec): 14.41 - samples/sec: 2502.41 - lr: 0.000004 - momentum: 0.000000 |
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2023-10-25 13:11:46,246 epoch 10 - iter 308/773 - loss 0.00484397 - time (sec): 18.88 - samples/sec: 2537.74 - lr: 0.000003 - momentum: 0.000000 |
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2023-10-25 13:11:50,725 epoch 10 - iter 385/773 - loss 0.00486479 - time (sec): 23.36 - samples/sec: 2583.19 - lr: 0.000003 - momentum: 0.000000 |
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2023-10-25 13:11:55,217 epoch 10 - iter 462/773 - loss 0.00448509 - time (sec): 27.85 - samples/sec: 2610.23 - lr: 0.000002 - momentum: 0.000000 |
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2023-10-25 13:11:59,647 epoch 10 - iter 539/773 - loss 0.00421530 - time (sec): 32.28 - samples/sec: 2666.27 - lr: 0.000002 - momentum: 0.000000 |
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2023-10-25 13:12:03,857 epoch 10 - iter 616/773 - loss 0.00437212 - time (sec): 36.49 - samples/sec: 2714.86 - lr: 0.000001 - momentum: 0.000000 |
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2023-10-25 13:12:08,105 epoch 10 - iter 693/773 - loss 0.00404879 - time (sec): 40.74 - samples/sec: 2740.99 - lr: 0.000001 - momentum: 0.000000 |
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2023-10-25 13:12:12,357 epoch 10 - iter 770/773 - loss 0.00377079 - time (sec): 44.99 - samples/sec: 2755.00 - lr: 0.000000 - momentum: 0.000000 |
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2023-10-25 13:12:12,511 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:12:12,512 EPOCH 10 done: loss 0.0038 - lr: 0.000000 |
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2023-10-25 13:12:15,102 DEV : loss 0.1328500360250473 - f1-score (micro avg) 0.7571 |
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2023-10-25 13:12:15,570 ---------------------------------------------------------------------------------------------------- |
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2023-10-25 13:12:15,571 Loading model from best epoch ... |
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2023-10-25 13:12:17,308 SequenceTagger predicts: Dictionary with 13 tags: O, S-LOC, B-LOC, E-LOC, I-LOC, S-BUILDING, B-BUILDING, E-BUILDING, I-BUILDING, S-STREET, B-STREET, E-STREET, I-STREET |
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2023-10-25 13:12:26,537 |
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Results: |
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- F-score (micro) 0.7861 |
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- F-score (macro) 0.6918 |
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- Accuracy 0.6688 |
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By class: |
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precision recall f1-score support |
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LOC 0.8186 0.8393 0.8288 946 |
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BUILDING 0.6193 0.5892 0.6039 185 |
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STREET 0.6429 0.6429 0.6429 56 |
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micro avg 0.7812 0.7911 0.7861 1187 |
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macro avg 0.6936 0.6905 0.6918 1187 |
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weighted avg 0.7792 0.7911 0.7850 1187 |
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2023-10-25 13:12:26,537 ---------------------------------------------------------------------------------------------------- |
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