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bertimbau-base-lener_br
This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on the lener_br dataset. It achieves the following results on the evaluation set:
- Loss: 0.2298
- Precision: 0.8501
- Recall: 0.9138
- F1: 0.8808
- Accuracy: 0.9693
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0686 | 1.0 | 1957 | 0.1399 | 0.7759 | 0.8669 | 0.8189 | 0.9641 |
| 0.0437 | 2.0 | 3914 | 0.1457 | 0.7997 | 0.8938 | 0.8441 | 0.9623 |
| 0.0313 | 3.0 | 5871 | 0.1675 | 0.8466 | 0.8744 | 0.8603 | 0.9651 |
| 0.0201 | 4.0 | 7828 | 0.1621 | 0.8713 | 0.8839 | 0.8775 | 0.9718 |
| 0.0137 | 5.0 | 9785 | 0.1811 | 0.7783 | 0.9159 | 0.8415 | 0.9645 |
| 0.0105 | 6.0 | 11742 | 0.1836 | 0.8568 | 0.9009 | 0.8783 | 0.9692 |
| 0.0105 | 7.0 | 13699 | 0.1649 | 0.8339 | 0.9125 | 0.8714 | 0.9725 |
| 0.0059 | 8.0 | 15656 | 0.2298 | 0.8501 | 0.9138 | 0.8808 | 0.9693 |
| 0.0051 | 9.0 | 17613 | 0.2210 | 0.8437 | 0.9045 | 0.8731 | 0.9693 |
| 0.0061 | 10.0 | 19570 | 0.2499 | 0.8627 | 0.8946 | 0.8784 | 0.9681 |
| 0.0041 | 11.0 | 21527 | 0.1985 | 0.8560 | 0.9052 | 0.8799 | 0.9720 |
| 0.003 | 12.0 | 23484 | 0.2204 | 0.8498 | 0.9065 | 0.8772 | 0.9699 |
| 0.0014 | 13.0 | 25441 | 0.2152 | 0.8425 | 0.9067 | 0.8734 | 0.9709 |
| 0.0005 | 14.0 | 27398 | 0.2317 | 0.8553 | 0.8987 | 0.8765 | 0.9705 |
| 0.0015 | 15.0 | 29355 | 0.2436 | 0.8543 | 0.8989 | 0.8760 | 0.9700 |
Framework versions
- Transformers 4.8.2
- Pytorch 1.9.0+cu102
- Datasets 1.9.0
- Tokenizers 0.10.3
