---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: DisTEMIST_bsc_test1
  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. -->

# DisTEMIST_bsc_test1

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: 0.1876
- Diso Precision: 0.7529
- Diso Recall: 0.7818
- Diso F1: 0.7671
- Diso Number: 1407
- Overall Precision: 0.7529
- Overall Recall: 0.7818
- Overall F1: 0.7671
- 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: 4e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=2.6e-09
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 73
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Diso Precision | Diso Recall | Diso F1 | Diso Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:-----------:|:-------:|:-----------:|:-----------------:|:--------------:|:----------:|:----------------:|
| 0.1734        | 1.0   | 997  | 0.1084          | 0.7166         | 0.6397      | 0.6759  | 1407        | 0.7166            | 0.6397         | 0.6759     | 0.9656           |
| 0.0589        | 2.0   | 1994 | 0.0896          | 0.7249         | 0.7662      | 0.7450  | 1407        | 0.7249            | 0.7662         | 0.7450     | 0.9725           |
| 0.0288        | 3.0   | 2991 | 0.1162          | 0.7199         | 0.7910      | 0.7538  | 1407        | 0.7199            | 0.7910         | 0.7538     | 0.9725           |
| 0.0163        | 4.0   | 3988 | 0.1267          | 0.7434         | 0.7783      | 0.7604  | 1407        | 0.7434            | 0.7783         | 0.7604     | 0.9731           |
| 0.0096        | 5.0   | 4985 | 0.1362          | 0.7406         | 0.7832      | 0.7613  | 1407        | 0.7406            | 0.7832         | 0.7613     | 0.9748           |
| 0.0047        | 6.0   | 5982 | 0.1573          | 0.7619         | 0.7711      | 0.7665  | 1407        | 0.7619            | 0.7711         | 0.7665     | 0.9745           |
| 0.0041        | 7.0   | 6979 | 0.1773          | 0.7083         | 0.7939      | 0.7487  | 1407        | 0.7083            | 0.7939         | 0.7487     | 0.9691           |
| 0.0019        | 8.0   | 7976 | 0.1682          | 0.7441         | 0.7811      | 0.7621  | 1407        | 0.7441            | 0.7811         | 0.7621     | 0.9741           |
| 0.0012        | 9.0   | 8973 | 0.1823          | 0.7507         | 0.7811      | 0.7656  | 1407        | 0.7507            | 0.7811         | 0.7656     | 0.9743           |
| 0.0004        | 10.0  | 9970 | 0.1876          | 0.7529         | 0.7818      | 0.7671  | 1407        | 0.7529            | 0.7818         | 0.7671     | 0.9744           |


### Framework versions

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