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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_explainability2
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_explainability2
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: 0.3811
- Roc Auc: 0.8939
- Ap Score: 0.7760
- Precision: 0.9146
- Recall: 0.8065
- F1: 0.8571
## 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: 3e-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 |
|:-------------:|:------:|:----:|:---------------:|:-------:|:--------:|:---------:|:------:|:------:|
| 0.3644 | 0.8475 | 100 | 0.2350 | 0.8402 | 0.6907 | 0.9028 | 0.6989 | 0.7879 |
| 0.1848 | 1.6949 | 200 | 0.2358 | 0.8765 | 0.7168 | 0.8588 | 0.7849 | 0.8202 |
| 0.1462 | 2.5424 | 300 | 0.2215 | 0.9021 | 0.7509 | 0.8571 | 0.8387 | 0.8478 |
| 0.1105 | 3.3898 | 400 | 0.2671 | 0.8778 | 0.7504 | 0.9114 | 0.7742 | 0.8372 |
| 0.079 | 4.2373 | 500 | 0.3124 | 0.8630 | 0.7338 | 0.92 | 0.7419 | 0.8214 |
| 0.0248 | 5.0847 | 600 | 0.3464 | 0.8765 | 0.7416 | 0.9 | 0.7742 | 0.8324 |
| 0.0127 | 5.9322 | 700 | 0.3822 | 0.8617 | 0.7248 | 0.9079 | 0.7419 | 0.8166 |
| 0.0089 | 6.7797 | 800 | 0.3625 | 0.8885 | 0.7674 | 0.9136 | 0.7957 | 0.8506 |
| 0.0042 | 7.6271 | 900 | 0.3643 | 0.8885 | 0.7674 | 0.9136 | 0.7957 | 0.8506 |
| 0.0052 | 8.4746 | 1000 | 0.3772 | 0.8939 | 0.7760 | 0.9146 | 0.8065 | 0.8571 |
| 0.0031 | 9.3220 | 1100 | 0.3811 | 0.8939 | 0.7760 | 0.9146 | 0.8065 | 0.8571 |
### Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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