---
license: apache-2.0
base_model: PlanTL-GOB-ES/bsc-bio-ehr-es
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: vih_explainability3
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# vih_explainability3

This model is a fine-tuned version of [PlanTL-GOB-ES/bsc-bio-ehr-es](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3951
- Roc Auc: 0.8213
- Ap Score: 0.7049
- Precision: 0.9836
- Recall: 0.6452
- F1: 0.7792

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Roc Auc | Ap Score | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:-------:|:--------:|:---------:|:------:|:------:|
| 0.4261        | 0.8475 | 100  | 0.3832          | 0.6129  | 0.3793   | 1.0       | 0.2258 | 0.3684 |
| 0.2405        | 1.6949 | 200  | 0.4736          | 0.6344  | 0.4138   | 1.0       | 0.2688 | 0.4237 |
| 0.2088        | 2.5424 | 300  | 0.3452          | 0.7729  | 0.6274   | 0.9808    | 0.5484 | 0.7034 |
| 0.2196        | 3.3898 | 400  | 0.3644          | 0.7151  | 0.5431   | 1.0       | 0.4301 | 0.6015 |
| 0.2068        | 4.2373 | 500  | 0.5156          | 0.6344  | 0.4138   | 1.0       | 0.2688 | 0.4237 |
| 0.1374        | 5.0847 | 600  | 0.3988          | 0.7944  | 0.6619   | 0.9821    | 0.5914 | 0.7383 |
| 0.1098        | 5.9322 | 700  | 0.3629          | 0.8051  | 0.6791   | 0.9828    | 0.6129 | 0.7550 |
| 0.0914        | 6.7797 | 800  | 0.3394          | 0.8240  | 0.6934   | 0.9531    | 0.6559 | 0.7771 |
| 0.088         | 7.6271 | 900  | 0.3612          | 0.8334  | 0.7009   | 0.9403    | 0.6774 | 0.7875 |
| 0.0787        | 8.4746 | 1000 | 0.3801          | 0.8213  | 0.7049   | 0.9836    | 0.6452 | 0.7792 |
| 0.0588        | 9.3220 | 1100 | 0.3951          | 0.8213  | 0.7049   | 0.9836    | 0.6452 | 0.7792 |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1