bertimbau-base-lener-br-finetuned-lener-br
This model is a fine-tuned version of Luciano/bertimbau-base-finetuned-lener-br on the lener_br dataset. It achieves the following results on the evaluation set:
- Loss: nan
- Precision: 0.8943
- Recall: 0.8970
- F1: 0.8956
- Accuracy: 0.9696
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 |
|---|---|---|---|---|---|---|---|
| 0.0678 | 1.0 | 1957 | nan | 0.8148 | 0.8882 | 0.8499 | 0.9689 |
| 0.0371 | 2.0 | 3914 | nan | 0.8347 | 0.9022 | 0.8671 | 0.9671 |
| 0.0242 | 3.0 | 5871 | nan | 0.8491 | 0.8905 | 0.8693 | 0.9716 |
| 0.0197 | 4.0 | 7828 | nan | 0.9014 | 0.8772 | 0.8892 | 0.9780 |
| 0.0135 | 5.0 | 9785 | nan | 0.8651 | 0.9060 | 0.8851 | 0.9765 |
| 0.013 | 6.0 | 11742 | nan | 0.8882 | 0.9054 | 0.8967 | 0.9767 |
| 0.0084 | 7.0 | 13699 | nan | 0.8559 | 0.9097 | 0.8820 | 0.9751 |
| 0.0069 | 8.0 | 15656 | nan | 0.8916 | 0.8828 | 0.8872 | 0.9696 |
| 0.0047 | 9.0 | 17613 | nan | 0.8964 | 0.8931 | 0.8948 | 0.9716 |
| 0.0028 | 10.0 | 19570 | nan | 0.8864 | 0.9047 | 0.8955 | 0.9691 |
| 0.0023 | 11.0 | 21527 | nan | 0.8860 | 0.9011 | 0.8935 | 0.9693 |
| 0.0009 | 12.0 | 23484 | nan | 0.8952 | 0.8987 | 0.8970 | 0.9686 |
| 0.0014 | 13.0 | 25441 | nan | 0.8929 | 0.8985 | 0.8957 | 0.9699 |
| 0.0025 | 14.0 | 27398 | nan | 0.8914 | 0.8981 | 0.8947 | 0.9700 |
| 0.001 | 15.0 | 29355 | nan | 0.8943 | 0.8970 | 0.8956 | 0.9696 |
Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1