---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: DISO_bsc_test
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# DISO_bsc_test

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: 0.0959
- Diso Precision: 0.7766
- Diso Recall: 0.7803
- Diso F1: 0.7784
- Diso Number: 4552
- Overall Precision: 0.7766
- Overall Recall: 0.7803
- Overall F1: 0.7784
- Overall Accuracy: 0.9744

## 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: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Diso Precision | Diso Recall | Diso F1 | Diso Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------------:|:-----------:|:-------:|:-----------:|:-----------------:|:--------------:|:----------:|:----------------:|
| 0.0849        | 1.0   | 2799  | 0.0734          | 0.7360         | 0.7676      | 0.7515  | 4552        | 0.7360            | 0.7676         | 0.7515     | 0.9726           |
| 0.0572        | 2.0   | 5598  | 0.0736          | 0.7674         | 0.7768      | 0.7721  | 4552        | 0.7674            | 0.7768         | 0.7721     | 0.9743           |
| 0.0462        | 3.0   | 8397  | 0.0836          | 0.7737         | 0.7707      | 0.7722  | 4552        | 0.7737            | 0.7707         | 0.7722     | 0.9736           |
| 0.0318        | 4.0   | 11196 | 0.0959          | 0.7766         | 0.7803      | 0.7784  | 4552        | 0.7766            | 0.7803         | 0.7784     | 0.9744           |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2