RigoBERTa-Clinical_es_symptom
This model is a fine-tuned version of IIC/RigoBERTa-Clinical on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0049
- Precision: 0.9854
- Recall: 0.9908
- F1: 0.9881
- Accuracy: 0.9983
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1790 | 1.0 | 739 | 0.0919 | 0.8265 | 0.8546 | 0.8403 | 0.9635 |
| 0.1143 | 2.0 | 1478 | 0.0648 | 0.8832 | 0.8979 | 0.8904 | 0.9751 |
| 0.0765 | 3.0 | 2217 | 0.0436 | 0.9203 | 0.9217 | 0.9210 | 0.9841 |
| 0.0631 | 4.0 | 2956 | 0.0294 | 0.9363 | 0.9532 | 0.9447 | 0.9902 |
| 0.0419 | 5.0 | 3695 | 0.0216 | 0.9517 | 0.9698 | 0.9607 | 0.9927 |
| 0.0342 | 6.0 | 4434 | 0.0165 | 0.9603 | 0.9774 | 0.9688 | 0.9943 |
| 0.0232 | 7.0 | 5173 | 0.0115 | 0.9757 | 0.9817 | 0.9787 | 0.9967 |
| 0.0202 | 8.0 | 5912 | 0.0081 | 0.9793 | 0.9890 | 0.9841 | 0.9976 |
| 0.0139 | 9.0 | 6651 | 0.0057 | 0.9847 | 0.9889 | 0.9868 | 0.9982 |
| 0.0120 | 10.0 | 7390 | 0.0049 | 0.9854 | 0.9908 | 0.9881 | 0.9983 |
Framework versions
- Transformers 5.4.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.4
- Tokenizers 0.22.2
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