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---
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
should probably proofread and complete it, then remove this comment. -->
# 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
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