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2023-10-17 10:25:39,666 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:25:39,667 Model: "SequenceTagger( |
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(embeddings): TransformerWordEmbeddings( |
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(model): ElectraModel( |
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(embeddings): ElectraEmbeddings( |
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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): ElectraEncoder( |
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(layer): ModuleList( |
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(0-11): 12 x ElectraLayer( |
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(attention): ElectraAttention( |
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(self): ElectraSelfAttention( |
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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): ElectraSelfOutput( |
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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): ElectraIntermediate( |
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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): ElectraOutput( |
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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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) |
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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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2023-10-17 10:25:39,668 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:25:39,668 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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2023-10-17 10:25:39,668 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:25:39,668 Train: 6183 sentences |
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2023-10-17 10:25:39,668 (train_with_dev=False, train_with_test=False) |
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2023-10-17 10:25:39,668 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:25:39,668 Training Params: |
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2023-10-17 10:25:39,668 - learning_rate: "5e-05" |
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2023-10-17 10:25:39,668 - mini_batch_size: "4" |
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2023-10-17 10:25:39,668 - max_epochs: "10" |
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2023-10-17 10:25:39,668 - shuffle: "True" |
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2023-10-17 10:25:39,668 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:25:39,668 Plugins: |
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2023-10-17 10:25:39,669 - TensorboardLogger |
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2023-10-17 10:25:39,669 - LinearScheduler | warmup_fraction: '0.1' |
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2023-10-17 10:25:39,669 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:25:39,669 Final evaluation on model from best epoch (best-model.pt) |
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2023-10-17 10:25:39,669 - metric: "('micro avg', 'f1-score')" |
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2023-10-17 10:25:39,669 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:25:39,669 Computation: |
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2023-10-17 10:25:39,669 - compute on device: cuda:0 |
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2023-10-17 10:25:39,669 - embedding storage: none |
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2023-10-17 10:25:39,669 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:25:39,669 Model training base path: "hmbench-topres19th/en-hmteams/teams-base-historic-multilingual-discriminator-bs4-wsFalse-e10-lr5e-05-poolingfirst-layers-1-crfFalse-2" |
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2023-10-17 10:25:39,669 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:25:39,669 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:25:39,669 Logging anything other than scalars to TensorBoard is currently not supported. |
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2023-10-17 10:25:51,632 epoch 1 - iter 154/1546 - loss 2.02180981 - time (sec): 11.96 - samples/sec: 944.73 - lr: 0.000005 - momentum: 0.000000 |
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2023-10-17 10:26:04,276 epoch 1 - iter 308/1546 - loss 1.05133169 - time (sec): 24.60 - samples/sec: 1008.11 - lr: 0.000010 - momentum: 0.000000 |
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2023-10-17 10:26:16,281 epoch 1 - iter 462/1546 - loss 0.75054260 - time (sec): 36.61 - samples/sec: 1031.68 - lr: 0.000015 - momentum: 0.000000 |
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2023-10-17 10:26:28,650 epoch 1 - iter 616/1546 - loss 0.59271900 - time (sec): 48.98 - samples/sec: 1032.05 - lr: 0.000020 - momentum: 0.000000 |
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2023-10-17 10:26:41,225 epoch 1 - iter 770/1546 - loss 0.49705880 - time (sec): 61.55 - samples/sec: 1028.74 - lr: 0.000025 - momentum: 0.000000 |
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2023-10-17 10:26:53,393 epoch 1 - iter 924/1546 - loss 0.43170337 - time (sec): 73.72 - samples/sec: 1033.06 - lr: 0.000030 - momentum: 0.000000 |
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2023-10-17 10:27:05,348 epoch 1 - iter 1078/1546 - loss 0.39066886 - time (sec): 85.68 - samples/sec: 1021.48 - lr: 0.000035 - momentum: 0.000000 |
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2023-10-17 10:27:17,415 epoch 1 - iter 1232/1546 - loss 0.35716844 - time (sec): 97.74 - samples/sec: 1020.75 - lr: 0.000040 - momentum: 0.000000 |
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2023-10-17 10:27:29,146 epoch 1 - iter 1386/1546 - loss 0.33123533 - time (sec): 109.47 - samples/sec: 1026.36 - lr: 0.000045 - momentum: 0.000000 |
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2023-10-17 10:27:40,598 epoch 1 - iter 1540/1546 - loss 0.31206315 - time (sec): 120.93 - samples/sec: 1024.74 - lr: 0.000050 - momentum: 0.000000 |
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2023-10-17 10:27:41,031 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:27:41,031 EPOCH 1 done: loss 0.3115 - lr: 0.000050 |
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2023-10-17 10:27:43,666 DEV : loss 0.07279833406209946 - f1-score (micro avg) 0.7049 |
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2023-10-17 10:27:43,693 saving best model |
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2023-10-17 10:27:44,227 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:27:55,853 epoch 2 - iter 154/1546 - loss 0.17648886 - time (sec): 11.62 - samples/sec: 1047.19 - lr: 0.000049 - momentum: 0.000000 |
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2023-10-17 10:28:07,775 epoch 2 - iter 308/1546 - loss 0.15188272 - time (sec): 23.55 - samples/sec: 1070.06 - lr: 0.000049 - momentum: 0.000000 |
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2023-10-17 10:28:19,828 epoch 2 - iter 462/1546 - loss 0.13981404 - time (sec): 35.60 - samples/sec: 1037.47 - lr: 0.000048 - momentum: 0.000000 |
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2023-10-17 10:28:32,332 epoch 2 - iter 616/1546 - loss 0.12814078 - time (sec): 48.10 - samples/sec: 1024.94 - lr: 0.000048 - momentum: 0.000000 |
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2023-10-17 10:28:44,172 epoch 2 - iter 770/1546 - loss 0.12573561 - time (sec): 59.94 - samples/sec: 1022.59 - lr: 0.000047 - momentum: 0.000000 |
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2023-10-17 10:28:56,254 epoch 2 - iter 924/1546 - loss 0.12073221 - time (sec): 72.03 - samples/sec: 1017.97 - lr: 0.000047 - momentum: 0.000000 |
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2023-10-17 10:29:09,100 epoch 2 - iter 1078/1546 - loss 0.11547940 - time (sec): 84.87 - samples/sec: 1013.64 - lr: 0.000046 - momentum: 0.000000 |
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2023-10-17 10:29:20,955 epoch 2 - iter 1232/1546 - loss 0.11335352 - time (sec): 96.73 - samples/sec: 1017.70 - lr: 0.000046 - momentum: 0.000000 |
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2023-10-17 10:29:32,654 epoch 2 - iter 1386/1546 - loss 0.11157211 - time (sec): 108.42 - samples/sec: 1024.63 - lr: 0.000045 - momentum: 0.000000 |
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2023-10-17 10:29:44,656 epoch 2 - iter 1540/1546 - loss 0.10827885 - time (sec): 120.43 - samples/sec: 1029.36 - lr: 0.000044 - momentum: 0.000000 |
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2023-10-17 10:29:45,108 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:29:45,108 EPOCH 2 done: loss 0.1081 - lr: 0.000044 |
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2023-10-17 10:29:48,007 DEV : loss 0.05769108608365059 - f1-score (micro avg) 0.7859 |
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2023-10-17 10:29:48,040 saving best model |
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2023-10-17 10:29:49,482 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:30:01,407 epoch 3 - iter 154/1546 - loss 0.09035284 - time (sec): 11.92 - samples/sec: 985.24 - lr: 0.000044 - momentum: 0.000000 |
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2023-10-17 10:30:12,820 epoch 3 - iter 308/1546 - loss 0.07445859 - time (sec): 23.33 - samples/sec: 1097.98 - lr: 0.000043 - momentum: 0.000000 |
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2023-10-17 10:30:24,703 epoch 3 - iter 462/1546 - loss 0.07415434 - time (sec): 35.22 - samples/sec: 1100.85 - lr: 0.000043 - momentum: 0.000000 |
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2023-10-17 10:30:37,609 epoch 3 - iter 616/1546 - loss 0.07540870 - time (sec): 48.12 - samples/sec: 1045.62 - lr: 0.000042 - momentum: 0.000000 |
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2023-10-17 10:30:50,460 epoch 3 - iter 770/1546 - loss 0.07301929 - time (sec): 60.97 - samples/sec: 1021.49 - lr: 0.000042 - momentum: 0.000000 |
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2023-10-17 10:31:04,196 epoch 3 - iter 924/1546 - loss 0.07303987 - time (sec): 74.71 - samples/sec: 1004.25 - lr: 0.000041 - momentum: 0.000000 |
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2023-10-17 10:31:15,649 epoch 3 - iter 1078/1546 - loss 0.07020216 - time (sec): 86.16 - samples/sec: 1010.69 - lr: 0.000041 - momentum: 0.000000 |
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2023-10-17 10:31:27,261 epoch 3 - iter 1232/1546 - loss 0.07010983 - time (sec): 97.78 - samples/sec: 1016.90 - lr: 0.000040 - momentum: 0.000000 |
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2023-10-17 10:31:39,005 epoch 3 - iter 1386/1546 - loss 0.06794363 - time (sec): 109.52 - samples/sec: 1025.10 - lr: 0.000039 - momentum: 0.000000 |
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2023-10-17 10:31:50,746 epoch 3 - iter 1540/1546 - loss 0.06707353 - time (sec): 121.26 - samples/sec: 1021.84 - lr: 0.000039 - momentum: 0.000000 |
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2023-10-17 10:31:51,242 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:31:51,242 EPOCH 3 done: loss 0.0670 - lr: 0.000039 |
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2023-10-17 10:31:54,247 DEV : loss 0.07943776994943619 - f1-score (micro avg) 0.8114 |
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2023-10-17 10:31:54,285 saving best model |
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2023-10-17 10:31:55,701 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:32:07,901 epoch 4 - iter 154/1546 - loss 0.04828653 - time (sec): 12.20 - samples/sec: 1063.56 - lr: 0.000038 - momentum: 0.000000 |
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2023-10-17 10:32:20,064 epoch 4 - iter 308/1546 - loss 0.05173450 - time (sec): 24.36 - samples/sec: 1039.44 - lr: 0.000038 - momentum: 0.000000 |
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2023-10-17 10:32:32,324 epoch 4 - iter 462/1546 - loss 0.04954644 - time (sec): 36.62 - samples/sec: 1016.86 - lr: 0.000037 - momentum: 0.000000 |
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2023-10-17 10:32:44,801 epoch 4 - iter 616/1546 - loss 0.05004385 - time (sec): 49.10 - samples/sec: 1003.51 - lr: 0.000037 - momentum: 0.000000 |
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2023-10-17 10:32:56,865 epoch 4 - iter 770/1546 - loss 0.04750404 - time (sec): 61.16 - samples/sec: 1016.02 - lr: 0.000036 - momentum: 0.000000 |
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2023-10-17 10:33:09,083 epoch 4 - iter 924/1546 - loss 0.04870217 - time (sec): 73.38 - samples/sec: 1014.04 - lr: 0.000036 - momentum: 0.000000 |
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2023-10-17 10:33:20,791 epoch 4 - iter 1078/1546 - loss 0.04965165 - time (sec): 85.09 - samples/sec: 1018.08 - lr: 0.000035 - momentum: 0.000000 |
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2023-10-17 10:33:32,692 epoch 4 - iter 1232/1546 - loss 0.04736677 - time (sec): 96.99 - samples/sec: 1026.67 - lr: 0.000034 - momentum: 0.000000 |
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2023-10-17 10:33:44,844 epoch 4 - iter 1386/1546 - loss 0.04811731 - time (sec): 109.14 - samples/sec: 1026.04 - lr: 0.000034 - momentum: 0.000000 |
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2023-10-17 10:33:57,129 epoch 4 - iter 1540/1546 - loss 0.04803105 - time (sec): 121.42 - samples/sec: 1019.68 - lr: 0.000033 - momentum: 0.000000 |
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2023-10-17 10:33:57,607 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:33:57,608 EPOCH 4 done: loss 0.0481 - lr: 0.000033 |
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2023-10-17 10:34:00,432 DEV : loss 0.0833667516708374 - f1-score (micro avg) 0.7711 |
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2023-10-17 10:34:00,460 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:34:12,396 epoch 5 - iter 154/1546 - loss 0.02385740 - time (sec): 11.93 - samples/sec: 1024.45 - lr: 0.000033 - momentum: 0.000000 |
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2023-10-17 10:34:24,347 epoch 5 - iter 308/1546 - loss 0.02748508 - time (sec): 23.89 - samples/sec: 1001.54 - lr: 0.000032 - momentum: 0.000000 |
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2023-10-17 10:34:36,363 epoch 5 - iter 462/1546 - loss 0.02582250 - time (sec): 35.90 - samples/sec: 995.55 - lr: 0.000032 - momentum: 0.000000 |
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2023-10-17 10:34:48,343 epoch 5 - iter 616/1546 - loss 0.02616104 - time (sec): 47.88 - samples/sec: 1005.06 - lr: 0.000031 - momentum: 0.000000 |
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2023-10-17 10:35:00,744 epoch 5 - iter 770/1546 - loss 0.03219186 - time (sec): 60.28 - samples/sec: 1003.30 - lr: 0.000031 - momentum: 0.000000 |
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2023-10-17 10:35:12,809 epoch 5 - iter 924/1546 - loss 0.03235715 - time (sec): 72.35 - samples/sec: 1007.34 - lr: 0.000030 - momentum: 0.000000 |
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2023-10-17 10:35:24,651 epoch 5 - iter 1078/1546 - loss 0.03225049 - time (sec): 84.19 - samples/sec: 1029.36 - lr: 0.000029 - momentum: 0.000000 |
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2023-10-17 10:35:36,841 epoch 5 - iter 1232/1546 - loss 0.03312944 - time (sec): 96.38 - samples/sec: 1028.66 - lr: 0.000029 - momentum: 0.000000 |
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2023-10-17 10:35:49,293 epoch 5 - iter 1386/1546 - loss 0.03394222 - time (sec): 108.83 - samples/sec: 1020.22 - lr: 0.000028 - momentum: 0.000000 |
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2023-10-17 10:36:01,342 epoch 5 - iter 1540/1546 - loss 0.03495607 - time (sec): 120.88 - samples/sec: 1024.69 - lr: 0.000028 - momentum: 0.000000 |
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2023-10-17 10:36:01,814 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:36:01,814 EPOCH 5 done: loss 0.0350 - lr: 0.000028 |
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2023-10-17 10:36:05,180 DEV : loss 0.110050730407238 - f1-score (micro avg) 0.7099 |
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2023-10-17 10:36:05,213 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:36:17,215 epoch 6 - iter 154/1546 - loss 0.03050029 - time (sec): 12.00 - samples/sec: 1034.82 - lr: 0.000027 - momentum: 0.000000 |
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2023-10-17 10:36:29,436 epoch 6 - iter 308/1546 - loss 0.02599671 - time (sec): 24.22 - samples/sec: 1030.57 - lr: 0.000027 - momentum: 0.000000 |
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2023-10-17 10:36:41,414 epoch 6 - iter 462/1546 - loss 0.02421473 - time (sec): 36.20 - samples/sec: 1038.52 - lr: 0.000026 - momentum: 0.000000 |
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2023-10-17 10:36:53,413 epoch 6 - iter 616/1546 - loss 0.02336062 - time (sec): 48.20 - samples/sec: 1040.54 - lr: 0.000026 - momentum: 0.000000 |
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2023-10-17 10:37:05,424 epoch 6 - iter 770/1546 - loss 0.02547084 - time (sec): 60.21 - samples/sec: 1032.66 - lr: 0.000025 - momentum: 0.000000 |
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2023-10-17 10:37:17,945 epoch 6 - iter 924/1546 - loss 0.02397867 - time (sec): 72.73 - samples/sec: 1024.75 - lr: 0.000024 - momentum: 0.000000 |
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2023-10-17 10:37:29,949 epoch 6 - iter 1078/1546 - loss 0.02277072 - time (sec): 84.73 - samples/sec: 1036.78 - lr: 0.000024 - momentum: 0.000000 |
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2023-10-17 10:37:41,864 epoch 6 - iter 1232/1546 - loss 0.02426498 - time (sec): 96.65 - samples/sec: 1029.50 - lr: 0.000023 - momentum: 0.000000 |
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2023-10-17 10:37:53,712 epoch 6 - iter 1386/1546 - loss 0.02385236 - time (sec): 108.50 - samples/sec: 1028.24 - lr: 0.000023 - momentum: 0.000000 |
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2023-10-17 10:38:05,568 epoch 6 - iter 1540/1546 - loss 0.02402382 - time (sec): 120.35 - samples/sec: 1028.83 - lr: 0.000022 - momentum: 0.000000 |
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2023-10-17 10:38:06,019 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:38:06,019 EPOCH 6 done: loss 0.0241 - lr: 0.000022 |
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2023-10-17 10:38:08,835 DEV : loss 0.09071236848831177 - f1-score (micro avg) 0.7718 |
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2023-10-17 10:38:08,863 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:38:20,993 epoch 7 - iter 154/1546 - loss 0.01858194 - time (sec): 12.13 - samples/sec: 1035.21 - lr: 0.000022 - momentum: 0.000000 |
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2023-10-17 10:38:33,142 epoch 7 - iter 308/1546 - loss 0.02029265 - time (sec): 24.28 - samples/sec: 1076.84 - lr: 0.000021 - momentum: 0.000000 |
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2023-10-17 10:38:44,918 epoch 7 - iter 462/1546 - loss 0.01874414 - time (sec): 36.05 - samples/sec: 1064.32 - lr: 0.000021 - momentum: 0.000000 |
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2023-10-17 10:38:56,851 epoch 7 - iter 616/1546 - loss 0.02012904 - time (sec): 47.99 - samples/sec: 1052.19 - lr: 0.000020 - momentum: 0.000000 |
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2023-10-17 10:39:08,577 epoch 7 - iter 770/1546 - loss 0.02056826 - time (sec): 59.71 - samples/sec: 1049.28 - lr: 0.000019 - momentum: 0.000000 |
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2023-10-17 10:39:20,396 epoch 7 - iter 924/1546 - loss 0.01990787 - time (sec): 71.53 - samples/sec: 1037.05 - lr: 0.000019 - momentum: 0.000000 |
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2023-10-17 10:39:32,595 epoch 7 - iter 1078/1546 - loss 0.02052998 - time (sec): 83.73 - samples/sec: 1028.28 - lr: 0.000018 - momentum: 0.000000 |
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2023-10-17 10:39:44,797 epoch 7 - iter 1232/1546 - loss 0.01888219 - time (sec): 95.93 - samples/sec: 1030.99 - lr: 0.000018 - momentum: 0.000000 |
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2023-10-17 10:39:56,820 epoch 7 - iter 1386/1546 - loss 0.01791790 - time (sec): 107.95 - samples/sec: 1035.40 - lr: 0.000017 - momentum: 0.000000 |
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2023-10-17 10:40:09,502 epoch 7 - iter 1540/1546 - loss 0.01840040 - time (sec): 120.64 - samples/sec: 1027.33 - lr: 0.000017 - momentum: 0.000000 |
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2023-10-17 10:40:10,068 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:40:10,068 EPOCH 7 done: loss 0.0185 - lr: 0.000017 |
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2023-10-17 10:40:13,083 DEV : loss 0.12031986564397812 - f1-score (micro avg) 0.7705 |
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2023-10-17 10:40:13,114 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:40:25,169 epoch 8 - iter 154/1546 - loss 0.01247555 - time (sec): 12.05 - samples/sec: 1025.95 - lr: 0.000016 - momentum: 0.000000 |
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2023-10-17 10:40:37,477 epoch 8 - iter 308/1546 - loss 0.00887144 - time (sec): 24.36 - samples/sec: 1038.46 - lr: 0.000016 - momentum: 0.000000 |
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2023-10-17 10:40:49,680 epoch 8 - iter 462/1546 - loss 0.00915473 - time (sec): 36.56 - samples/sec: 1015.25 - lr: 0.000015 - momentum: 0.000000 |
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2023-10-17 10:41:02,185 epoch 8 - iter 616/1546 - loss 0.01189933 - time (sec): 49.07 - samples/sec: 1008.89 - lr: 0.000014 - momentum: 0.000000 |
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2023-10-17 10:41:14,290 epoch 8 - iter 770/1546 - loss 0.01107024 - time (sec): 61.17 - samples/sec: 1018.87 - lr: 0.000014 - momentum: 0.000000 |
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2023-10-17 10:41:26,129 epoch 8 - iter 924/1546 - loss 0.01086037 - time (sec): 73.01 - samples/sec: 1027.72 - lr: 0.000013 - momentum: 0.000000 |
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2023-10-17 10:41:38,145 epoch 8 - iter 1078/1546 - loss 0.01157159 - time (sec): 85.03 - samples/sec: 1024.92 - lr: 0.000013 - momentum: 0.000000 |
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2023-10-17 10:41:49,914 epoch 8 - iter 1232/1546 - loss 0.01193759 - time (sec): 96.80 - samples/sec: 1024.57 - lr: 0.000012 - momentum: 0.000000 |
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2023-10-17 10:42:02,221 epoch 8 - iter 1386/1546 - loss 0.01219084 - time (sec): 109.10 - samples/sec: 1023.58 - lr: 0.000012 - momentum: 0.000000 |
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2023-10-17 10:42:13,995 epoch 8 - iter 1540/1546 - loss 0.01168510 - time (sec): 120.88 - samples/sec: 1023.56 - lr: 0.000011 - momentum: 0.000000 |
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2023-10-17 10:42:14,461 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:42:14,461 EPOCH 8 done: loss 0.0117 - lr: 0.000011 |
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2023-10-17 10:42:17,363 DEV : loss 0.11697618663311005 - f1-score (micro avg) 0.8008 |
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2023-10-17 10:42:17,397 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:42:29,121 epoch 9 - iter 154/1546 - loss 0.01140863 - time (sec): 11.72 - samples/sec: 1045.07 - lr: 0.000011 - momentum: 0.000000 |
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2023-10-17 10:42:40,816 epoch 9 - iter 308/1546 - loss 0.01020266 - time (sec): 23.42 - samples/sec: 1032.47 - lr: 0.000010 - momentum: 0.000000 |
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2023-10-17 10:42:52,458 epoch 9 - iter 462/1546 - loss 0.00903518 - time (sec): 35.06 - samples/sec: 1077.02 - lr: 0.000009 - momentum: 0.000000 |
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2023-10-17 10:43:04,002 epoch 9 - iter 616/1546 - loss 0.00887521 - time (sec): 46.60 - samples/sec: 1062.22 - lr: 0.000009 - momentum: 0.000000 |
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2023-10-17 10:43:15,609 epoch 9 - iter 770/1546 - loss 0.00783009 - time (sec): 58.21 - samples/sec: 1056.47 - lr: 0.000008 - momentum: 0.000000 |
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2023-10-17 10:43:28,043 epoch 9 - iter 924/1546 - loss 0.00793805 - time (sec): 70.64 - samples/sec: 1039.01 - lr: 0.000008 - momentum: 0.000000 |
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2023-10-17 10:43:39,954 epoch 9 - iter 1078/1546 - loss 0.00743572 - time (sec): 82.55 - samples/sec: 1035.87 - lr: 0.000007 - momentum: 0.000000 |
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2023-10-17 10:43:51,915 epoch 9 - iter 1232/1546 - loss 0.00757961 - time (sec): 94.52 - samples/sec: 1050.24 - lr: 0.000007 - momentum: 0.000000 |
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2023-10-17 10:44:04,164 epoch 9 - iter 1386/1546 - loss 0.00743361 - time (sec): 106.76 - samples/sec: 1040.78 - lr: 0.000006 - momentum: 0.000000 |
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2023-10-17 10:44:16,128 epoch 9 - iter 1540/1546 - loss 0.00756154 - time (sec): 118.73 - samples/sec: 1044.29 - lr: 0.000006 - momentum: 0.000000 |
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2023-10-17 10:44:16,573 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:44:16,574 EPOCH 9 done: loss 0.0076 - lr: 0.000006 |
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2023-10-17 10:44:19,531 DEV : loss 0.12403418123722076 - f1-score (micro avg) 0.7884 |
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2023-10-17 10:44:19,562 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:44:31,581 epoch 10 - iter 154/1546 - loss 0.00254844 - time (sec): 12.02 - samples/sec: 1087.04 - lr: 0.000005 - momentum: 0.000000 |
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2023-10-17 10:44:43,680 epoch 10 - iter 308/1546 - loss 0.00244110 - time (sec): 24.12 - samples/sec: 1018.42 - lr: 0.000004 - momentum: 0.000000 |
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2023-10-17 10:44:55,700 epoch 10 - iter 462/1546 - loss 0.00305097 - time (sec): 36.14 - samples/sec: 1005.43 - lr: 0.000004 - momentum: 0.000000 |
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2023-10-17 10:45:07,998 epoch 10 - iter 616/1546 - loss 0.00292169 - time (sec): 48.43 - samples/sec: 1012.33 - lr: 0.000003 - momentum: 0.000000 |
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2023-10-17 10:45:20,453 epoch 10 - iter 770/1546 - loss 0.00318972 - time (sec): 60.89 - samples/sec: 1004.67 - lr: 0.000003 - momentum: 0.000000 |
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2023-10-17 10:45:32,649 epoch 10 - iter 924/1546 - loss 0.00372386 - time (sec): 73.08 - samples/sec: 1001.91 - lr: 0.000002 - momentum: 0.000000 |
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2023-10-17 10:45:44,939 epoch 10 - iter 1078/1546 - loss 0.00392698 - time (sec): 85.37 - samples/sec: 1008.88 - lr: 0.000002 - momentum: 0.000000 |
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2023-10-17 10:45:57,060 epoch 10 - iter 1232/1546 - loss 0.00386062 - time (sec): 97.50 - samples/sec: 1028.14 - lr: 0.000001 - momentum: 0.000000 |
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2023-10-17 10:46:09,103 epoch 10 - iter 1386/1546 - loss 0.00402196 - time (sec): 109.54 - samples/sec: 1020.51 - lr: 0.000001 - momentum: 0.000000 |
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2023-10-17 10:46:20,872 epoch 10 - iter 1540/1546 - loss 0.00428314 - time (sec): 121.31 - samples/sec: 1021.41 - lr: 0.000000 - momentum: 0.000000 |
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2023-10-17 10:46:21,321 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:46:21,322 EPOCH 10 done: loss 0.0043 - lr: 0.000000 |
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2023-10-17 10:46:24,218 DEV : loss 0.1269896924495697 - f1-score (micro avg) 0.7866 |
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2023-10-17 10:46:24,806 ---------------------------------------------------------------------------------------------------- |
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2023-10-17 10:46:24,808 Loading model from best epoch ... |
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2023-10-17 10:46:27,155 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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2023-10-17 10:46:36,273 |
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Results: |
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- F-score (micro) 0.7831 |
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- F-score (macro) 0.6698 |
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- Accuracy 0.6639 |
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By class: |
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precision recall f1-score support |
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LOC 0.7952 0.8700 0.8309 946 |
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BUILDING 0.6107 0.4919 0.5449 185 |
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STREET 0.7111 0.5714 0.6337 56 |
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micro avg 0.7697 0.7970 0.7831 1187 |
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macro avg 0.7057 0.6444 0.6698 1187 |
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weighted avg 0.7625 0.7970 0.7770 1187 |
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2023-10-17 10:46:36,274 ---------------------------------------------------------------------------------------------------- |
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