| 2022-02-04 12:18:14,159 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 12:18:14,161 Model: "SequenceTagger( | |
| (embeddings): TransformerWordEmbeddings( | |
| (model): CamembertModel( | |
| (embeddings): RobertaEmbeddings( | |
| (word_embeddings): Embedding(32005, 768, padding_idx=1) | |
| (position_embeddings): Embedding(514, 768, padding_idx=1) | |
| (token_type_embeddings): Embedding(1, 768) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (encoder): RobertaEncoder( | |
| (layer): ModuleList( | |
| (0): RobertaLayer( | |
| (attention): RobertaAttention( | |
| (self): RobertaSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): RobertaSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): RobertaIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| ) | |
| (output): RobertaOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (1): RobertaLayer( | |
| (attention): RobertaAttention( | |
| (self): RobertaSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): RobertaSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): RobertaIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| ) | |
| (output): RobertaOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (2): RobertaLayer( | |
| (attention): RobertaAttention( | |
| (self): RobertaSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): RobertaSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): RobertaIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| ) | |
| (output): RobertaOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (3): RobertaLayer( | |
| (attention): RobertaAttention( | |
| (self): RobertaSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): RobertaSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): RobertaIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| ) | |
| (output): RobertaOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (4): RobertaLayer( | |
| (attention): RobertaAttention( | |
| (self): RobertaSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): RobertaSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): RobertaIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| ) | |
| (output): RobertaOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (5): RobertaLayer( | |
| (attention): RobertaAttention( | |
| (self): RobertaSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): RobertaSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): RobertaIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| ) | |
| (output): RobertaOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (6): RobertaLayer( | |
| (attention): RobertaAttention( | |
| (self): RobertaSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): RobertaSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): RobertaIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| ) | |
| (output): RobertaOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (7): RobertaLayer( | |
| (attention): RobertaAttention( | |
| (self): RobertaSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): RobertaSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): RobertaIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| ) | |
| (output): RobertaOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (8): RobertaLayer( | |
| (attention): RobertaAttention( | |
| (self): RobertaSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): RobertaSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): RobertaIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| ) | |
| (output): RobertaOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (9): RobertaLayer( | |
| (attention): RobertaAttention( | |
| (self): RobertaSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): RobertaSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): RobertaIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| ) | |
| (output): RobertaOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (10): RobertaLayer( | |
| (attention): RobertaAttention( | |
| (self): RobertaSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): RobertaSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): RobertaIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| ) | |
| (output): RobertaOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (11): RobertaLayer( | |
| (attention): RobertaAttention( | |
| (self): RobertaSelfAttention( | |
| (query): Linear(in_features=768, out_features=768, bias=True) | |
| (key): Linear(in_features=768, out_features=768, bias=True) | |
| (value): Linear(in_features=768, out_features=768, bias=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| (output): RobertaSelfOutput( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| (intermediate): RobertaIntermediate( | |
| (dense): Linear(in_features=768, out_features=3072, bias=True) | |
| ) | |
| (output): RobertaOutput( | |
| (dense): Linear(in_features=3072, out_features=768, bias=True) | |
| (LayerNorm): LayerNorm((768,), eps=1e-05, elementwise_affine=True) | |
| (dropout): Dropout(p=0.1, inplace=False) | |
| ) | |
| ) | |
| ) | |
| ) | |
| (pooler): RobertaPooler( | |
| (dense): Linear(in_features=768, out_features=768, bias=True) | |
| (activation): Tanh() | |
| ) | |
| ) | |
| ) | |
| (word_dropout): WordDropout(p=0.05) | |
| (locked_dropout): LockedDropout(p=0.5) | |
| (linear): Linear(in_features=768, out_features=18, bias=True) | |
| (beta): 1.0 | |
| (weights): None | |
| (weight_tensor) None | |
| )" | |
| 2022-02-04 12:18:14,167 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 12:18:14,167 Corpus: "Corpus: 126973 train + 7037 dev + 7090 test sentences" | |
| 2022-02-04 12:18:14,167 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 12:18:14,167 Parameters: | |
| 2022-02-04 12:18:14,167 - learning_rate: "5e-05" | |
| 2022-02-04 12:18:14,167 - mini_batch_size: "16" | |
| 2022-02-04 12:18:14,167 - patience: "3" | |
| 2022-02-04 12:18:14,167 - anneal_factor: "0.5" | |
| 2022-02-04 12:18:14,167 - max_epochs: "10" | |
| 2022-02-04 12:18:14,167 - shuffle: "True" | |
| 2022-02-04 12:18:14,167 - train_with_dev: "False" | |
| 2022-02-04 12:18:14,167 - batch_growth_annealing: "False" | |
| 2022-02-04 12:18:14,167 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 12:18:14,167 Model training base path: "resources/taggers/ner-camembert" | |
| 2022-02-04 12:18:14,167 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 12:18:14,167 Device: cuda:0 | |
| 2022-02-04 12:18:14,167 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 12:18:14,167 Embeddings storage mode: none | |
| 2022-02-04 12:18:14,170 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 12:25:23,397 epoch 1 - iter 793/7936 - loss 1.64849782 - samples/sec: 29.56 - lr: 0.000005 | |
| 2022-02-04 12:33:59,649 epoch 1 - iter 1586/7936 - loss 1.11222779 - samples/sec: 24.58 - lr: 0.000010 | |
| 2022-02-04 12:41:09,132 epoch 1 - iter 2379/7936 - loss 0.85257016 - samples/sec: 29.55 - lr: 0.000015 | |
| 2022-02-04 12:47:44,896 epoch 1 - iter 3172/7936 - loss 0.71981753 - samples/sec: 32.07 - lr: 0.000020 | |
| 2022-02-04 12:55:15,449 epoch 1 - iter 3965/7936 - loss 0.60512907 - samples/sec: 28.16 - lr: 0.000025 | |
| 2022-02-04 13:02:35,238 epoch 1 - iter 4758/7936 - loss 0.52903622 - samples/sec: 28.85 - lr: 0.000030 | |
| 2022-02-04 13:09:27,012 epoch 1 - iter 5551/7936 - loss 0.48171220 - samples/sec: 30.82 - lr: 0.000035 | |
| 2022-02-04 13:15:53,083 epoch 1 - iter 6344/7936 - loss 0.44948661 - samples/sec: 32.87 - lr: 0.000040 | |
| 2022-02-04 13:22:02,650 epoch 1 - iter 7137/7936 - loss 0.42228564 - samples/sec: 34.34 - lr: 0.000045 | |
| 2022-02-04 13:28:59,445 epoch 1 - iter 7930/7936 - loss 0.39366725 - samples/sec: 30.45 - lr: 0.000050 | |
| 2022-02-04 13:29:03,026 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 13:29:03,028 EPOCH 1 done: loss 0.3935 - lr 0.0000500 | |
| 2022-02-04 13:32:00,102 DEV : loss 0.038586683571338654 - f1-score (micro avg) 0.8195 | |
| 2022-02-04 13:32:00,155 BAD EPOCHS (no improvement): 4 | |
| 2022-02-04 13:32:00,156 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 13:39:12,612 epoch 2 - iter 793/7936 - loss 0.14931520 - samples/sec: 29.34 - lr: 0.000049 | |
| 2022-02-04 13:46:36,550 epoch 2 - iter 1586/7936 - loss 0.14672871 - samples/sec: 28.58 - lr: 0.000049 | |
| 2022-02-04 13:53:49,885 epoch 2 - iter 2379/7936 - loss 0.14547274 - samples/sec: 29.28 - lr: 0.000048 | |
| 2022-02-04 14:01:13,739 epoch 2 - iter 3172/7936 - loss 0.14418846 - samples/sec: 28.59 - lr: 0.000048 | |
| 2022-02-04 14:08:30,985 epoch 2 - iter 3965/7936 - loss 0.14265825 - samples/sec: 29.02 - lr: 0.000047 | |
| 2022-02-04 14:15:46,742 epoch 2 - iter 4758/7936 - loss 0.14086599 - samples/sec: 29.12 - lr: 0.000047 | |
| 2022-02-04 14:23:11,181 epoch 2 - iter 5551/7936 - loss 0.13927378 - samples/sec: 28.55 - lr: 0.000046 | |
| 2022-02-04 14:30:19,706 epoch 2 - iter 6344/7936 - loss 0.13799042 - samples/sec: 29.61 - lr: 0.000046 | |
| 2022-02-04 14:37:30,554 epoch 2 - iter 7137/7936 - loss 0.13666296 - samples/sec: 29.45 - lr: 0.000045 | |
| 2022-02-04 14:44:52,886 epoch 2 - iter 7930/7936 - loss 0.13525042 - samples/sec: 28.69 - lr: 0.000044 | |
| 2022-02-04 14:44:56,060 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 14:44:56,062 EPOCH 2 done: loss 0.1352 - lr 0.0000444 | |
| 2022-02-04 14:47:40,950 DEV : loss 0.015217592008411884 - f1-score (micro avg) 0.9164 | |
| 2022-02-04 14:47:41,011 BAD EPOCHS (no improvement): 4 | |
| 2022-02-04 14:47:41,014 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 14:55:04,697 epoch 3 - iter 793/7936 - loss 0.11742558 - samples/sec: 28.60 - lr: 0.000044 | |
| 2022-02-04 15:02:16,388 epoch 3 - iter 1586/7936 - loss 0.11679901 - samples/sec: 29.40 - lr: 0.000043 | |
| 2022-02-04 15:09:29,924 epoch 3 - iter 2379/7936 - loss 0.11557918 - samples/sec: 29.27 - lr: 0.000043 | |
| 2022-02-04 15:16:54,356 epoch 3 - iter 3172/7936 - loss 0.11469700 - samples/sec: 28.55 - lr: 0.000042 | |
| 2022-02-04 15:24:11,817 epoch 3 - iter 3965/7936 - loss 0.11351908 - samples/sec: 29.01 - lr: 0.000042 | |
| 2022-02-04 15:31:20,620 epoch 3 - iter 4758/7936 - loss 0.11266101 - samples/sec: 29.59 - lr: 0.000041 | |
| 2022-02-04 15:38:42,882 epoch 3 - iter 5551/7936 - loss 0.11158730 - samples/sec: 28.69 - lr: 0.000041 | |
| 2022-02-04 15:45:50,317 epoch 3 - iter 6344/7936 - loss 0.11067669 - samples/sec: 29.69 - lr: 0.000040 | |
| 2022-02-04 15:53:16,035 epoch 3 - iter 7137/7936 - loss 0.10955013 - samples/sec: 28.47 - lr: 0.000039 | |
| 2022-02-04 16:00:25,858 epoch 3 - iter 7930/7936 - loss 0.10859645 - samples/sec: 29.52 - lr: 0.000039 | |
| 2022-02-04 16:00:29,034 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 16:00:29,035 EPOCH 3 done: loss 0.1086 - lr 0.0000389 | |
| 2022-02-04 16:03:24,201 DEV : loss 0.015040190890431404 - f1-score (micro avg) 0.9276 | |
| 2022-02-04 16:03:24,261 BAD EPOCHS (no improvement): 4 | |
| 2022-02-04 16:03:24,262 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 16:10:35,356 epoch 4 - iter 793/7936 - loss 0.09491620 - samples/sec: 29.44 - lr: 0.000038 | |
| 2022-02-04 16:17:46,476 epoch 4 - iter 1586/7936 - loss 0.09400900 - samples/sec: 29.43 - lr: 0.000038 | |
| 2022-02-04 16:25:10,503 epoch 4 - iter 2379/7936 - loss 0.09355228 - samples/sec: 28.58 - lr: 0.000037 | |
| 2022-02-04 16:32:21,829 epoch 4 - iter 3172/7936 - loss 0.09257257 - samples/sec: 29.42 - lr: 0.000037 | |
| 2022-02-04 16:39:34,717 epoch 4 - iter 3965/7936 - loss 0.09178491 - samples/sec: 29.31 - lr: 0.000036 | |
| 2022-02-04 16:46:54,536 epoch 4 - iter 4758/7936 - loss 0.09102086 - samples/sec: 28.85 - lr: 0.000036 | |
| 2022-02-04 16:54:08,674 epoch 4 - iter 5551/7936 - loss 0.09026061 - samples/sec: 29.23 - lr: 0.000035 | |
| 2022-02-04 17:01:24,799 epoch 4 - iter 6344/7936 - loss 0.08942621 - samples/sec: 29.10 - lr: 0.000034 | |
| 2022-02-04 17:08:44,577 epoch 4 - iter 7137/7936 - loss 0.08868927 - samples/sec: 28.85 - lr: 0.000034 | |
| 2022-02-04 17:15:57,678 epoch 4 - iter 7930/7936 - loss 0.08790466 - samples/sec: 29.30 - lr: 0.000033 | |
| 2022-02-04 17:16:00,787 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 17:16:00,790 EPOCH 4 done: loss 0.0879 - lr 0.0000333 | |
| 2022-02-04 17:18:55,805 DEV : loss 0.015710221603512764 - f1-score (micro avg) 0.9308 | |
| 2022-02-04 17:18:55,865 BAD EPOCHS (no improvement): 4 | |
| 2022-02-04 17:18:55,873 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 17:26:02,969 epoch 5 - iter 793/7936 - loss 0.07683748 - samples/sec: 29.71 - lr: 0.000033 | |
| 2022-02-04 17:33:13,355 epoch 5 - iter 1586/7936 - loss 0.07621969 - samples/sec: 29.49 - lr: 0.000032 | |
| 2022-02-04 17:40:38,247 epoch 5 - iter 2379/7936 - loss 0.07573593 - samples/sec: 28.52 - lr: 0.000032 | |
| 2022-02-04 17:47:40,269 epoch 5 - iter 3172/7936 - loss 0.07524740 - samples/sec: 30.07 - lr: 0.000031 | |
| 2022-02-04 17:54:59,036 epoch 5 - iter 3965/7936 - loss 0.07449799 - samples/sec: 28.92 - lr: 0.000031 | |
| 2022-02-04 18:02:03,686 epoch 5 - iter 4758/7936 - loss 0.07405311 - samples/sec: 29.88 - lr: 0.000030 | |
| 2022-02-04 18:09:11,646 epoch 5 - iter 5551/7936 - loss 0.07340830 - samples/sec: 29.65 - lr: 0.000029 | |
| 2022-02-04 18:16:27,240 epoch 5 - iter 6344/7936 - loss 0.07271787 - samples/sec: 29.13 - lr: 0.000029 | |
| 2022-02-04 18:23:29,669 epoch 5 - iter 7137/7936 - loss 0.07217288 - samples/sec: 30.04 - lr: 0.000028 | |
| 2022-02-04 18:30:30,597 epoch 5 - iter 7930/7936 - loss 0.07166288 - samples/sec: 30.15 - lr: 0.000028 | |
| 2022-02-04 18:30:33,919 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 18:30:33,920 EPOCH 5 done: loss 0.0717 - lr 0.0000278 | |
| 2022-02-04 18:33:23,923 DEV : loss 0.017801353707909584 - f1-score (micro avg) 0.9319 | |
| 2022-02-04 18:33:23,983 BAD EPOCHS (no improvement): 4 | |
| 2022-02-04 18:33:23,983 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 18:40:28,017 epoch 6 - iter 793/7936 - loss 0.06265627 - samples/sec: 29.93 - lr: 0.000027 | |
| 2022-02-04 18:47:46,740 epoch 6 - iter 1586/7936 - loss 0.06168821 - samples/sec: 28.92 - lr: 0.000027 | |
| 2022-02-04 18:54:59,429 epoch 6 - iter 2379/7936 - loss 0.06137959 - samples/sec: 29.33 - lr: 0.000026 | |
| 2022-02-04 19:02:08,367 epoch 6 - iter 3172/7936 - loss 0.06101991 - samples/sec: 29.58 - lr: 0.000026 | |
| 2022-02-04 19:09:34,369 epoch 6 - iter 3965/7936 - loss 0.06073221 - samples/sec: 28.45 - lr: 0.000025 | |
| 2022-02-04 19:16:53,646 epoch 6 - iter 4758/7936 - loss 0.06031513 - samples/sec: 28.89 - lr: 0.000024 | |
| 2022-02-04 19:24:05,427 epoch 6 - iter 5551/7936 - loss 0.05997466 - samples/sec: 29.39 - lr: 0.000024 | |
| 2022-02-04 19:31:27,470 epoch 6 - iter 6344/7936 - loss 0.05952743 - samples/sec: 28.71 - lr: 0.000023 | |
| 2022-02-04 19:38:37,449 epoch 6 - iter 7137/7936 - loss 0.05906427 - samples/sec: 29.51 - lr: 0.000023 | |
| 2022-02-04 19:46:02,608 epoch 6 - iter 7930/7936 - loss 0.05868560 - samples/sec: 28.51 - lr: 0.000022 | |
| 2022-02-04 19:46:05,790 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 19:46:05,791 EPOCH 6 done: loss 0.0587 - lr 0.0000222 | |
| 2022-02-04 19:48:52,058 DEV : loss 0.018429730087518692 - f1-score (micro avg) 0.9371 | |
| 2022-02-04 19:48:52,117 BAD EPOCHS (no improvement): 4 | |
| 2022-02-04 19:48:52,118 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 19:56:15,841 epoch 7 - iter 793/7936 - loss 0.05186660 - samples/sec: 28.60 - lr: 0.000022 | |
| 2022-02-04 20:03:27,574 epoch 7 - iter 1586/7936 - loss 0.05230029 - samples/sec: 29.39 - lr: 0.000021 | |
| 2022-02-04 20:10:42,349 epoch 7 - iter 2379/7936 - loss 0.05178480 - samples/sec: 29.19 - lr: 0.000021 | |
| 2022-02-04 20:18:09,822 epoch 7 - iter 3172/7936 - loss 0.05114746 - samples/sec: 28.36 - lr: 0.000020 | |
| 2022-02-04 20:25:23,574 epoch 7 - iter 3965/7936 - loss 0.05080701 - samples/sec: 29.26 - lr: 0.000019 | |
| 2022-02-04 20:32:39,287 epoch 7 - iter 4758/7936 - loss 0.05039880 - samples/sec: 29.12 - lr: 0.000019 | |
| 2022-02-04 20:40:04,807 epoch 7 - iter 5551/7936 - loss 0.05020234 - samples/sec: 28.48 - lr: 0.000018 | |
| 2022-02-04 20:47:17,356 epoch 7 - iter 6344/7936 - loss 0.04984342 - samples/sec: 29.34 - lr: 0.000018 | |
| 2022-02-04 20:54:31,673 epoch 7 - iter 7137/7936 - loss 0.04955538 - samples/sec: 29.22 - lr: 0.000017 | |
| 2022-02-04 21:01:58,187 epoch 7 - iter 7930/7936 - loss 0.04921375 - samples/sec: 28.42 - lr: 0.000017 | |
| 2022-02-04 21:02:01,071 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 21:02:01,071 EPOCH 7 done: loss 0.0492 - lr 0.0000167 | |
| 2022-02-04 21:04:47,460 DEV : loss 0.02109825611114502 - f1-score (micro avg) 0.9362 | |
| 2022-02-04 21:04:47,519 BAD EPOCHS (no improvement): 4 | |
| 2022-02-04 21:04:47,519 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 21:12:13,992 epoch 8 - iter 793/7936 - loss 0.04468006 - samples/sec: 28.42 - lr: 0.000016 | |
| 2022-02-04 21:19:25,811 epoch 8 - iter 1586/7936 - loss 0.04434977 - samples/sec: 29.39 - lr: 0.000016 | |
| 2022-02-04 21:26:35,161 epoch 8 - iter 2379/7936 - loss 0.04431108 - samples/sec: 29.56 - lr: 0.000015 | |
| 2022-02-04 21:33:55,512 epoch 8 - iter 3172/7936 - loss 0.04408371 - samples/sec: 28.82 - lr: 0.000014 | |
| 2022-02-04 21:41:09,449 epoch 8 - iter 3965/7936 - loss 0.04390607 - samples/sec: 29.24 - lr: 0.000014 | |
| 2022-02-04 21:48:30,449 epoch 8 - iter 4758/7936 - loss 0.04368218 - samples/sec: 28.77 - lr: 0.000013 | |
| 2022-02-04 21:55:47,346 epoch 8 - iter 5551/7936 - loss 0.04350544 - samples/sec: 29.05 - lr: 0.000013 | |
| 2022-02-04 22:03:02,107 epoch 8 - iter 6344/7936 - loss 0.04321482 - samples/sec: 29.19 - lr: 0.000012 | |
| 2022-02-04 22:10:29,225 epoch 8 - iter 7137/7936 - loss 0.04299359 - samples/sec: 28.38 - lr: 0.000012 | |
| 2022-02-04 22:17:46,915 epoch 8 - iter 7930/7936 - loss 0.04275655 - samples/sec: 28.99 - lr: 0.000011 | |
| 2022-02-04 22:17:50,251 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 22:17:50,252 EPOCH 8 done: loss 0.0428 - lr 0.0000111 | |
| 2022-02-04 22:20:46,443 DEV : loss 0.02112417109310627 - f1-score (micro avg) 0.9396 | |
| 2022-02-04 22:20:46,502 BAD EPOCHS (no improvement): 4 | |
| 2022-02-04 22:20:46,502 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 22:27:54,677 epoch 9 - iter 793/7936 - loss 0.03874630 - samples/sec: 29.64 - lr: 0.000011 | |
| 2022-02-04 22:35:07,034 epoch 9 - iter 1586/7936 - loss 0.03916791 - samples/sec: 29.35 - lr: 0.000010 | |
| 2022-02-04 22:42:33,861 epoch 9 - iter 2379/7936 - loss 0.03903771 - samples/sec: 28.40 - lr: 0.000009 | |
| 2022-02-04 22:49:45,768 epoch 9 - iter 3172/7936 - loss 0.03915089 - samples/sec: 29.38 - lr: 0.000009 | |
| 2022-02-04 22:56:49,271 epoch 9 - iter 3965/7936 - loss 0.03903752 - samples/sec: 29.96 - lr: 0.000008 | |
| 2022-02-04 23:04:02,033 epoch 9 - iter 4758/7936 - loss 0.03886980 - samples/sec: 29.32 - lr: 0.000008 | |
| 2022-02-04 23:11:05,006 epoch 9 - iter 5551/7936 - loss 0.03870274 - samples/sec: 30.00 - lr: 0.000007 | |
| 2022-02-04 23:18:05,622 epoch 9 - iter 6344/7936 - loss 0.03860323 - samples/sec: 30.17 - lr: 0.000007 | |
| 2022-02-04 23:25:20,470 epoch 9 - iter 7137/7936 - loss 0.03844156 - samples/sec: 29.18 - lr: 0.000006 | |
| 2022-02-04 23:32:20,810 epoch 9 - iter 7930/7936 - loss 0.03839073 - samples/sec: 30.19 - lr: 0.000006 | |
| 2022-02-04 23:32:23,941 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 23:32:23,942 EPOCH 9 done: loss 0.0384 - lr 0.0000056 | |
| 2022-02-04 23:35:14,351 DEV : loss 0.02171432413160801 - f1-score (micro avg) 0.9419 | |
| 2022-02-04 23:35:14,411 BAD EPOCHS (no improvement): 4 | |
| 2022-02-04 23:35:14,412 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 23:42:16,230 epoch 10 - iter 793/7936 - loss 0.03646154 - samples/sec: 30.08 - lr: 0.000005 | |
| 2022-02-04 23:49:27,305 epoch 10 - iter 1586/7936 - loss 0.03635515 - samples/sec: 29.44 - lr: 0.000004 | |
| 2022-02-04 23:56:27,850 epoch 10 - iter 2379/7936 - loss 0.03662968 - samples/sec: 30.17 - lr: 0.000004 | |
| 2022-02-05 00:03:30,598 epoch 10 - iter 3172/7936 - loss 0.03640152 - samples/sec: 30.02 - lr: 0.000003 | |
| 2022-02-05 00:10:46,058 epoch 10 - iter 3965/7936 - loss 0.03636994 - samples/sec: 29.14 - lr: 0.000003 | |
| 2022-02-05 00:17:50,999 epoch 10 - iter 4758/7936 - loss 0.03636800 - samples/sec: 29.86 - lr: 0.000002 | |
| 2022-02-05 00:24:51,167 epoch 10 - iter 5551/7936 - loss 0.03625499 - samples/sec: 30.20 - lr: 0.000002 | |
| 2022-02-05 00:32:07,970 epoch 10 - iter 6344/7936 - loss 0.03625737 - samples/sec: 29.05 - lr: 0.000001 | |
| 2022-02-05 00:39:14,867 epoch 10 - iter 7137/7936 - loss 0.03618156 - samples/sec: 29.73 - lr: 0.000001 | |
| 2022-02-05 00:46:17,991 epoch 10 - iter 7930/7936 - loss 0.03611184 - samples/sec: 29.99 - lr: 0.000000 | |
| 2022-02-05 00:46:21,120 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 00:46:21,123 EPOCH 10 done: loss 0.0361 - lr 0.0000000 | |
| 2022-02-05 00:49:11,421 DEV : loss 0.023424603044986725 - f1-score (micro avg) 0.9417 | |
| 2022-02-05 00:49:11,486 BAD EPOCHS (no improvement): 4 | |
| 2022-02-05 00:49:12,641 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-05 00:49:12,643 Testing using last state of model ... | |
| 2022-02-05 00:52:03,154 0.9303 0.9309 0.9306 0.8856 | |
| 2022-02-05 00:52:03,155 | |
| Results: | |
| - F-score (micro) 0.9306 | |
| - F-score (macro) 0.9057 | |
| - Accuracy 0.8856 | |
| By class: | |
| precision recall f1-score support | |
| pers 0.9373 0.9236 0.9304 2734 | |
| loc 0.9140 0.9371 0.9254 1384 | |
| amount 0.9840 0.9840 0.9840 250 | |
| time 0.9447 0.9407 0.9427 236 | |
| func 0.9209 0.9143 0.9176 140 | |
| org 0.8364 0.9388 0.8846 49 | |
| prod 0.7742 0.8889 0.8276 27 | |
| event 0.8333 0.8333 0.8333 12 | |
| micro avg 0.9303 0.9309 0.9306 4832 | |
| macro avg 0.8931 0.9201 0.9057 4832 | |
| weighted avg 0.9307 0.9309 0.9307 4832 | |
| samples avg 0.8856 0.8856 0.8856 4832 | |
| 2022-02-05 00:52:03,155 ---------------------------------------------------------------------------------------------------- | |