Disease_Identification_RoBERTa_fine_tuned_Testing
This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-base-biomedical-clinical-es] (https://huggingface.co/PlanTL-GOB-ES/roberta-base-biomedical-clinical-es) on the [DisTEMIST dataset] (https://temu.bsc.es/distemist/). This is a result of the PhD dissertation of Antonio Tamayo. It achieves the following results on the evaluation set:
- Loss: 0.1665
- Precision: 0.7235
- Recall: 0.7528
- F1: 0.7378
- Accuracy: 0.9727
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0897 | 1.0 | 1504 | 0.0885 | 0.6534 | 0.6868 | 0.6697 | 0.9693 |
| 0.0626 | 2.0 | 3008 | 0.0899 | 0.6654 | 0.7532 | 0.7066 | 0.9687 |
| 0.0421 | 3.0 | 4512 | 0.1010 | 0.7121 | 0.7204 | 0.7162 | 0.9717 |
| 0.0268 | 4.0 | 6016 | 0.1180 | 0.7318 | 0.7427 | 0.7372 | 0.9725 |
| 0.0166 | 5.0 | 7520 | 0.1438 | 0.7225 | 0.7450 | 0.7336 | 0.9722 |
| 0.0086 | 6.0 | 9024 | 0.1603 | 0.7179 | 0.7532 | 0.7351 | 0.9724 |
| 0.0056 | 7.0 | 10528 | 0.1665 | 0.7235 | 0.7528 | 0.7378 | 0.9727 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3