| 2022-02-04 12:53:17,467 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 12:53:17,468 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=51, bias=True) | |
| (beta): 1.0 | |
| (weights): None | |
| (weight_tensor) None | |
| )" | |
| 2022-02-04 12:53:17,506 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 12:53:17,506 Corpus: "Corpus: 5642 train + 195 dev + 649 test sentences" | |
| 2022-02-04 12:53:17,506 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 12:53:17,506 Parameters: | |
| 2022-02-04 12:53:17,506 - learning_rate: "5e-06" | |
| 2022-02-04 12:53:17,506 - mini_batch_size: "32" | |
| 2022-02-04 12:53:17,506 - patience: "3" | |
| 2022-02-04 12:53:17,506 - anneal_factor: "0.5" | |
| 2022-02-04 12:53:17,506 - max_epochs: "10" | |
| 2022-02-04 12:53:17,506 - shuffle: "True" | |
| 2022-02-04 12:53:17,506 - train_with_dev: "False" | |
| 2022-02-04 12:53:17,506 - batch_growth_annealing: "False" | |
| 2022-02-04 12:53:17,506 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 12:53:17,506 Model training base path: "resources/taggers/pos-camembert" | |
| 2022-02-04 12:53:17,506 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 12:53:17,511 Device: cuda:0 | |
| 2022-02-04 12:53:17,511 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 12:53:17,511 Embeddings storage mode: none | |
| 2022-02-04 12:53:17,513 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 12:53:38,315 epoch 1 - iter 17/177 - loss 3.96872255 - samples/sec: 26.15 - lr: 0.000000 | |
| 2022-02-04 12:53:54,561 epoch 1 - iter 34/177 - loss 3.96629180 - samples/sec: 33.49 - lr: 0.000001 | |
| 2022-02-04 12:54:11,140 epoch 1 - iter 51/177 - loss 3.95985736 - samples/sec: 32.82 - lr: 0.000001 | |
| 2022-02-04 12:54:27,471 epoch 1 - iter 68/177 - loss 3.95248851 - samples/sec: 33.31 - lr: 0.000002 | |
| 2022-02-04 12:54:44,574 epoch 1 - iter 85/177 - loss 3.94223845 - samples/sec: 31.81 - lr: 0.000002 | |
| 2022-02-04 12:54:59,811 epoch 1 - iter 102/177 - loss 3.93034373 - samples/sec: 35.71 - lr: 0.000003 | |
| 2022-02-04 12:55:17,140 epoch 1 - iter 119/177 - loss 3.91667895 - samples/sec: 31.39 - lr: 0.000003 | |
| 2022-02-04 12:55:33,245 epoch 1 - iter 136/177 - loss 3.90088222 - samples/sec: 33.78 - lr: 0.000004 | |
| 2022-02-04 12:55:48,743 epoch 1 - iter 153/177 - loss 3.87766994 - samples/sec: 35.11 - lr: 0.000004 | |
| 2022-02-04 12:56:06,269 epoch 1 - iter 170/177 - loss 3.84880099 - samples/sec: 31.04 - lr: 0.000005 | |
| 2022-02-04 12:56:12,033 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 12:56:12,033 EPOCH 1 done: loss 3.8419 - lr 0.0000050 | |
| 2022-02-04 12:56:18,260 DEV : loss 3.509683847427368 - f1-score (micro avg) 0.3053 | |
| 2022-02-04 12:56:18,262 BAD EPOCHS (no improvement): 4 | |
| 2022-02-04 12:56:18,285 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 12:56:35,575 epoch 2 - iter 17/177 - loss 3.54034313 - samples/sec: 31.47 - lr: 0.000005 | |
| 2022-02-04 12:56:52,475 epoch 2 - iter 34/177 - loss 3.50300407 - samples/sec: 32.19 - lr: 0.000005 | |
| 2022-02-04 12:57:09,058 epoch 2 - iter 51/177 - loss 3.46864739 - samples/sec: 32.81 - lr: 0.000005 | |
| 2022-02-04 12:57:25,624 epoch 2 - iter 68/177 - loss 3.43125430 - samples/sec: 32.84 - lr: 0.000005 | |
| 2022-02-04 12:57:42,941 epoch 2 - iter 85/177 - loss 3.39270879 - samples/sec: 31.42 - lr: 0.000005 | |
| 2022-02-04 12:57:59,153 epoch 2 - iter 102/177 - loss 3.35791389 - samples/sec: 33.56 - lr: 0.000005 | |
| 2022-02-04 12:58:16,864 epoch 2 - iter 119/177 - loss 3.32573531 - samples/sec: 30.72 - lr: 0.000005 | |
| 2022-02-04 12:58:34,354 epoch 2 - iter 136/177 - loss 3.29370429 - samples/sec: 31.11 - lr: 0.000005 | |
| 2022-02-04 12:58:51,116 epoch 2 - iter 153/177 - loss 3.26367901 - samples/sec: 32.46 - lr: 0.000005 | |
| 2022-02-04 12:59:08,117 epoch 2 - iter 170/177 - loss 3.23382669 - samples/sec: 32.00 - lr: 0.000004 | |
| 2022-02-04 12:59:15,072 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 12:59:15,074 EPOCH 2 done: loss 3.2228 - lr 0.0000044 | |
| 2022-02-04 12:59:20,452 DEV : loss 2.775869846343994 - f1-score (micro avg) 0.6141 | |
| 2022-02-04 12:59:20,455 BAD EPOCHS (no improvement): 4 | |
| 2022-02-04 12:59:20,455 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 12:59:38,069 epoch 3 - iter 17/177 - loss 2.92343717 - samples/sec: 30.89 - lr: 0.000004 | |
| 2022-02-04 12:59:54,400 epoch 3 - iter 34/177 - loss 2.90201388 - samples/sec: 33.32 - lr: 0.000004 | |
| 2022-02-04 13:00:12,150 epoch 3 - iter 51/177 - loss 2.88495451 - samples/sec: 30.65 - lr: 0.000004 | |
| 2022-02-04 13:00:28,960 epoch 3 - iter 68/177 - loss 2.86475060 - samples/sec: 32.37 - lr: 0.000004 | |
| 2022-02-04 13:00:47,016 epoch 3 - iter 85/177 - loss 2.84779479 - samples/sec: 30.13 - lr: 0.000004 | |
| 2022-02-04 13:01:03,811 epoch 3 - iter 102/177 - loss 2.83018073 - samples/sec: 32.40 - lr: 0.000004 | |
| 2022-02-04 13:01:19,598 epoch 3 - iter 119/177 - loss 2.81577196 - samples/sec: 34.47 - lr: 0.000004 | |
| 2022-02-04 13:01:36,746 epoch 3 - iter 136/177 - loss 2.80310518 - samples/sec: 31.73 - lr: 0.000004 | |
| 2022-02-04 13:01:53,532 epoch 3 - iter 153/177 - loss 2.79075673 - samples/sec: 32.41 - lr: 0.000004 | |
| 2022-02-04 13:02:11,809 epoch 3 - iter 170/177 - loss 2.77624103 - samples/sec: 29.77 - lr: 0.000004 | |
| 2022-02-04 13:02:17,990 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 13:02:17,991 EPOCH 3 done: loss 2.7701 - lr 0.0000039 | |
| 2022-02-04 13:02:23,777 DEV : loss 2.410931348800659 - f1-score (micro avg) 0.819 | |
| 2022-02-04 13:02:23,780 BAD EPOCHS (no improvement): 4 | |
| 2022-02-04 13:02:23,781 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 13:02:41,231 epoch 4 - iter 17/177 - loss 2.60188784 - samples/sec: 31.18 - lr: 0.000004 | |
| 2022-02-04 13:02:58,635 epoch 4 - iter 34/177 - loss 2.59095213 - samples/sec: 31.26 - lr: 0.000004 | |
| 2022-02-04 13:03:15,040 epoch 4 - iter 51/177 - loss 2.58502577 - samples/sec: 33.17 - lr: 0.000004 | |
| 2022-02-04 13:03:32,700 epoch 4 - iter 68/177 - loss 2.57149732 - samples/sec: 30.81 - lr: 0.000004 | |
| 2022-02-04 13:03:49,889 epoch 4 - iter 85/177 - loss 2.55924475 - samples/sec: 31.65 - lr: 0.000004 | |
| 2022-02-04 13:04:07,257 epoch 4 - iter 102/177 - loss 2.54972860 - samples/sec: 31.33 - lr: 0.000004 | |
| 2022-02-04 13:04:24,141 epoch 4 - iter 119/177 - loss 2.54070048 - samples/sec: 32.23 - lr: 0.000004 | |
| 2022-02-04 13:04:40,320 epoch 4 - iter 136/177 - loss 2.53210863 - samples/sec: 33.69 - lr: 0.000003 | |
| 2022-02-04 13:04:57,281 epoch 4 - iter 153/177 - loss 2.52441237 - samples/sec: 32.08 - lr: 0.000003 | |
| 2022-02-04 13:05:15,246 epoch 4 - iter 170/177 - loss 2.51520228 - samples/sec: 30.29 - lr: 0.000003 | |
| 2022-02-04 13:05:21,452 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 13:05:21,458 EPOCH 4 done: loss 2.5123 - lr 0.0000033 | |
| 2022-02-04 13:05:27,295 DEV : loss 2.1908302307128906 - f1-score (micro avg) 0.8605 | |
| 2022-02-04 13:05:27,310 BAD EPOCHS (no improvement): 4 | |
| 2022-02-04 13:05:27,310 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 13:05:44,024 epoch 5 - iter 17/177 - loss 2.39887737 - samples/sec: 32.55 - lr: 0.000003 | |
| 2022-02-04 13:06:01,687 epoch 5 - iter 34/177 - loss 2.39948538 - samples/sec: 30.80 - lr: 0.000003 | |
| 2022-02-04 13:06:19,664 epoch 5 - iter 51/177 - loss 2.40078878 - samples/sec: 30.29 - lr: 0.000003 | |
| 2022-02-04 13:06:36,241 epoch 5 - iter 68/177 - loss 2.39524823 - samples/sec: 32.93 - lr: 0.000003 | |
| 2022-02-04 13:06:52,683 epoch 5 - iter 85/177 - loss 2.38764769 - samples/sec: 33.17 - lr: 0.000003 | |
| 2022-02-04 13:07:09,718 epoch 5 - iter 102/177 - loss 2.38104055 - samples/sec: 31.94 - lr: 0.000003 | |
| 2022-02-04 13:07:26,578 epoch 5 - iter 119/177 - loss 2.37384530 - samples/sec: 32.29 - lr: 0.000003 | |
| 2022-02-04 13:07:42,599 epoch 5 - iter 136/177 - loss 2.36823710 - samples/sec: 33.96 - lr: 0.000003 | |
| 2022-02-04 13:08:00,031 epoch 5 - iter 153/177 - loss 2.36030726 - samples/sec: 31.25 - lr: 0.000003 | |
| 2022-02-04 13:08:17,779 epoch 5 - iter 170/177 - loss 2.35368343 - samples/sec: 30.72 - lr: 0.000003 | |
| 2022-02-04 13:08:24,110 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 13:08:24,111 EPOCH 5 done: loss 2.3509 - lr 0.0000028 | |
| 2022-02-04 13:08:30,298 DEV : loss 2.0516607761383057 - f1-score (micro avg) 0.8737 | |
| 2022-02-04 13:08:30,301 BAD EPOCHS (no improvement): 4 | |
| 2022-02-04 13:08:30,301 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 13:08:46,667 epoch 6 - iter 17/177 - loss 2.27743160 - samples/sec: 33.25 - lr: 0.000003 | |
| 2022-02-04 13:09:04,814 epoch 6 - iter 34/177 - loss 2.27286852 - samples/sec: 29.99 - lr: 0.000003 | |
| 2022-02-04 13:09:21,239 epoch 6 - iter 51/177 - loss 2.27175336 - samples/sec: 33.23 - lr: 0.000003 | |
| 2022-02-04 13:09:38,163 epoch 6 - iter 68/177 - loss 2.26491131 - samples/sec: 32.15 - lr: 0.000003 | |
| 2022-02-04 13:09:54,338 epoch 6 - iter 85/177 - loss 2.25999023 - samples/sec: 33.65 - lr: 0.000003 | |
| 2022-02-04 13:10:12,270 epoch 6 - iter 102/177 - loss 2.25580949 - samples/sec: 30.38 - lr: 0.000002 | |
| 2022-02-04 13:10:29,245 epoch 6 - iter 119/177 - loss 2.25275307 - samples/sec: 32.13 - lr: 0.000002 | |
| 2022-02-04 13:10:46,065 epoch 6 - iter 136/177 - loss 2.24661845 - samples/sec: 32.40 - lr: 0.000002 | |
| 2022-02-04 13:11:03,357 epoch 6 - iter 153/177 - loss 2.24241040 - samples/sec: 31.47 - lr: 0.000002 | |
| 2022-02-04 13:11:22,211 epoch 6 - iter 170/177 - loss 2.23773462 - samples/sec: 28.87 - lr: 0.000002 | |
| 2022-02-04 13:11:28,309 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 13:11:28,321 EPOCH 6 done: loss 2.2366 - lr 0.0000022 | |
| 2022-02-04 13:11:34,136 DEV : loss 1.9612011909484863 - f1-score (micro avg) 0.884 | |
| 2022-02-04 13:11:34,150 BAD EPOCHS (no improvement): 4 | |
| 2022-02-04 13:11:34,151 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 13:11:50,446 epoch 7 - iter 17/177 - loss 2.19566504 - samples/sec: 33.39 - lr: 0.000002 | |
| 2022-02-04 13:12:06,851 epoch 7 - iter 34/177 - loss 2.19802945 - samples/sec: 33.21 - lr: 0.000002 | |
| 2022-02-04 13:12:23,401 epoch 7 - iter 51/177 - loss 2.19405535 - samples/sec: 32.88 - lr: 0.000002 | |
| 2022-02-04 13:12:41,303 epoch 7 - iter 68/177 - loss 2.19162087 - samples/sec: 30.39 - lr: 0.000002 | |
| 2022-02-04 13:12:58,144 epoch 7 - iter 85/177 - loss 2.18471516 - samples/sec: 32.35 - lr: 0.000002 | |
| 2022-02-04 13:13:16,467 epoch 7 - iter 102/177 - loss 2.18080579 - samples/sec: 29.75 - lr: 0.000002 | |
| 2022-02-04 13:13:34,031 epoch 7 - iter 119/177 - loss 2.17936921 - samples/sec: 31.00 - lr: 0.000002 | |
| 2022-02-04 13:13:51,077 epoch 7 - iter 136/177 - loss 2.17514038 - samples/sec: 32.02 - lr: 0.000002 | |
| 2022-02-04 13:14:07,857 epoch 7 - iter 153/177 - loss 2.17141812 - samples/sec: 32.48 - lr: 0.000002 | |
| 2022-02-04 13:14:25,422 epoch 7 - iter 170/177 - loss 2.16711471 - samples/sec: 30.99 - lr: 0.000002 | |
| 2022-02-04 13:14:31,227 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 13:14:31,228 EPOCH 7 done: loss 2.1662 - lr 0.0000017 | |
| 2022-02-04 13:14:37,035 DEV : loss 1.8981177806854248 - f1-score (micro avg) 0.9008 | |
| 2022-02-04 13:14:37,049 BAD EPOCHS (no improvement): 4 | |
| 2022-02-04 13:14:37,050 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 13:14:54,867 epoch 8 - iter 17/177 - loss 2.13839948 - samples/sec: 30.54 - lr: 0.000002 | |
| 2022-02-04 13:15:11,283 epoch 8 - iter 34/177 - loss 2.13301605 - samples/sec: 33.16 - lr: 0.000002 | |
| 2022-02-04 13:15:28,761 epoch 8 - iter 51/177 - loss 2.12335776 - samples/sec: 31.15 - lr: 0.000002 | |
| 2022-02-04 13:15:44,480 epoch 8 - iter 68/177 - loss 2.12525500 - samples/sec: 34.61 - lr: 0.000001 | |
| 2022-02-04 13:16:01,084 epoch 8 - iter 85/177 - loss 2.12100353 - samples/sec: 32.77 - lr: 0.000001 | |
| 2022-02-04 13:16:17,945 epoch 8 - iter 102/177 - loss 2.12081652 - samples/sec: 32.27 - lr: 0.000001 | |
| 2022-02-04 13:16:34,469 epoch 8 - iter 119/177 - loss 2.11872473 - samples/sec: 32.93 - lr: 0.000001 | |
| 2022-02-04 13:16:50,308 epoch 8 - iter 136/177 - loss 2.11635062 - samples/sec: 34.35 - lr: 0.000001 | |
| 2022-02-04 13:17:07,313 epoch 8 - iter 153/177 - loss 2.11371370 - samples/sec: 32.00 - lr: 0.000001 | |
| 2022-02-04 13:17:25,553 epoch 8 - iter 170/177 - loss 2.11100152 - samples/sec: 29.83 - lr: 0.000001 | |
| 2022-02-04 13:17:33,472 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 13:17:33,473 EPOCH 8 done: loss 2.1112 - lr 0.0000011 | |
| 2022-02-04 13:17:39,308 DEV : loss 1.8548760414123535 - f1-score (micro avg) 0.9117 | |
| 2022-02-04 13:17:39,311 BAD EPOCHS (no improvement): 4 | |
| 2022-02-04 13:17:39,311 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 13:17:56,622 epoch 9 - iter 17/177 - loss 2.06819398 - samples/sec: 31.43 - lr: 0.000001 | |
| 2022-02-04 13:18:13,360 epoch 9 - iter 34/177 - loss 2.07590305 - samples/sec: 32.51 - lr: 0.000001 | |
| 2022-02-04 13:18:31,366 epoch 9 - iter 51/177 - loss 2.07666788 - samples/sec: 30.22 - lr: 0.000001 | |
| 2022-02-04 13:18:49,983 epoch 9 - iter 68/177 - loss 2.07961625 - samples/sec: 29.23 - lr: 0.000001 | |
| 2022-02-04 13:19:06,239 epoch 9 - iter 85/177 - loss 2.08063462 - samples/sec: 33.47 - lr: 0.000001 | |
| 2022-02-04 13:19:23,068 epoch 9 - iter 102/177 - loss 2.08002246 - samples/sec: 32.33 - lr: 0.000001 | |
| 2022-02-04 13:19:40,188 epoch 9 - iter 119/177 - loss 2.07956869 - samples/sec: 31.78 - lr: 0.000001 | |
| 2022-02-04 13:19:57,482 epoch 9 - iter 136/177 - loss 2.07835867 - samples/sec: 31.47 - lr: 0.000001 | |
| 2022-02-04 13:20:14,155 epoch 9 - iter 153/177 - loss 2.07750905 - samples/sec: 32.64 - lr: 0.000001 | |
| 2022-02-04 13:20:31,533 epoch 9 - iter 170/177 - loss 2.07545212 - samples/sec: 31.31 - lr: 0.000001 | |
| 2022-02-04 13:20:37,466 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 13:20:37,468 EPOCH 9 done: loss 2.0759 - lr 0.0000006 | |
| 2022-02-04 13:20:43,299 DEV : loss 1.830302357673645 - f1-score (micro avg) 0.9161 | |
| 2022-02-04 13:20:43,314 BAD EPOCHS (no improvement): 4 | |
| 2022-02-04 13:20:43,314 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 13:21:00,247 epoch 10 - iter 17/177 - loss 2.06625894 - samples/sec: 32.13 - lr: 0.000001 | |
| 2022-02-04 13:21:16,847 epoch 10 - iter 34/177 - loss 2.06850742 - samples/sec: 32.78 - lr: 0.000000 | |
| 2022-02-04 13:21:34,047 epoch 10 - iter 51/177 - loss 2.06653386 - samples/sec: 31.68 - lr: 0.000000 | |
| 2022-02-04 13:21:50,597 epoch 10 - iter 68/177 - loss 2.06650174 - samples/sec: 32.88 - lr: 0.000000 | |
| 2022-02-04 13:22:07,286 epoch 10 - iter 85/177 - loss 2.06409229 - samples/sec: 32.61 - lr: 0.000000 | |
| 2022-02-04 13:22:25,744 epoch 10 - iter 102/177 - loss 2.06162033 - samples/sec: 29.48 - lr: 0.000000 | |
| 2022-02-04 13:22:43,419 epoch 10 - iter 119/177 - loss 2.06248176 - samples/sec: 30.78 - lr: 0.000000 | |
| 2022-02-04 13:22:59,502 epoch 10 - iter 136/177 - loss 2.06392395 - samples/sec: 33.83 - lr: 0.000000 | |
| 2022-02-04 13:23:16,396 epoch 10 - iter 153/177 - loss 2.06446242 - samples/sec: 32.21 - lr: 0.000000 | |
| 2022-02-04 13:23:33,136 epoch 10 - iter 170/177 - loss 2.06210437 - samples/sec: 32.50 - lr: 0.000000 | |
| 2022-02-04 13:23:40,551 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 13:23:40,552 EPOCH 10 done: loss 2.0624 - lr 0.0000000 | |
| 2022-02-04 13:23:46,365 DEV : loss 1.8217284679412842 - f1-score (micro avg) 0.9195 | |
| 2022-02-04 13:23:46,367 BAD EPOCHS (no improvement): 4 | |
| 2022-02-04 13:23:47,542 ---------------------------------------------------------------------------------------------------- | |
| 2022-02-04 13:23:47,544 Testing using last state of model ... | |
| 2022-02-04 13:24:07,461 0.9181 0.9181 0.9181 0.9181 | |
| 2022-02-04 13:24:07,462 | |
| Results: | |
| - F-score (micro) 0.9181 | |
| - F-score (macro) 0.439 | |
| - Accuracy 0.9181 | |
| By class: | |
| precision recall f1-score support | |
| NOMcom 0.9530 0.9808 0.9667 2130 | |
| VERcjg 0.9683 0.9935 0.9807 1535 | |
| PRE 0.8411 0.9940 0.9112 1331 | |
| PROper 0.9253 0.9963 0.9595 1368 | |
| PONfbl 0.9824 0.9993 0.9908 1341 | |
| ADVgen 0.8179 0.8276 0.8227 841 | |
| PONfrt 0.9721 1.0000 0.9859 662 | |
| DETdef 0.9393 0.9967 0.9672 606 | |
| ADJqua 0.8289 0.9400 0.8810 500 | |
| VERinf 0.9706 0.9960 0.9831 497 | |
| DETpos 0.9791 0.9979 0.9884 469 | |
| CONcoo 0.9645 0.9935 0.9788 465 | |
| CONsub 0.7437 0.9846 0.8473 389 | |
| VERppe 0.9042 0.9408 0.9221 321 | |
| DETndf 0.7270 0.9959 0.8405 246 | |
| NOMpro 0.9485 0.8340 0.8876 265 | |
| PROrel 0.9398 0.7519 0.8354 270 | |
| ADVneg 0.9577 0.7528 0.8430 271 | |
| DETdem 0.9934 0.9742 0.9837 155 | |
| PROind 1.0000 0.4894 0.6571 188 | |
| PROadv 0.9000 0.8108 0.8531 111 | |
| PROdem 1.0000 0.6387 0.7795 119 | |
| DETind 0.8000 0.7347 0.7660 98 | |
| PRE.DETdef 0.0000 0.0000 0.0000 183 | |
| VERppa 0.0000 0.0000 0.0000 67 | |
| PROimp 0.0000 0.0000 0.0000 54 | |
| INJ 0.0000 0.0000 0.0000 35 | |
| DETcar 0.0000 0.0000 0.0000 31 | |
| ADJind 0.0000 0.0000 0.0000 30 | |
| PROint 0.0000 0.0000 0.0000 22 | |
| ADJcar 0.0000 0.0000 0.0000 21 | |
| PROcar 0.0000 0.0000 0.0000 18 | |
| DETrel 0.0000 0.0000 0.0000 16 | |
| ADJord 0.0000 0.0000 0.0000 16 | |
| PONpga 0.0000 0.0000 0.0000 16 | |
| PROpos 0.0000 0.0000 0.0000 14 | |
| PONpdr 0.0000 0.0000 0.0000 13 | |
| DETint 0.0000 0.0000 0.0000 10 | |
| PONpxx 0.0000 0.0000 0.0000 6 | |
| ADVint 0.0000 0.0000 0.0000 5 | |
| PRE.PROrel 0.0000 0.0000 0.0000 2 | |
| latin 0.0000 0.0000 0.0000 2 | |
| PROord 0.0000 0.0000 0.0000 1 | |
| PRE.PROdem 0.0000 0.0000 0.0000 1 | |
| PRE.NOMcom 0.0000 0.0000 0.0000 1 | |
| ETR 0.0000 0.0000 0.0000 1 | |
| ADVsub 0.0000 0.0000 0.0000 1 | |
| micro avg 0.9181 0.9181 0.9181 14744 | |
| macro avg 0.4480 0.4388 0.4390 14744 | |
| weighted avg 0.8876 0.9181 0.8991 14744 | |
| samples avg 0.9181 0.9181 0.9181 14744 | |
| 2022-02-04 13:24:07,477 ---------------------------------------------------------------------------------------------------- | |