---
license: cc-by-4.0
base_model: bertin-project/bertin-roberta-base-spanish
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: my-model-Bertin-Area
  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. -->

# my-model-Bertin-Area

This model is a fine-tuned version of [bertin-project/bertin-roberta-base-spanish](https://huggingface.co/bertin-project/bertin-roberta-base-spanish) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0387
- Accuracy: 0.6403
- F1: 0.6388
- Precision: 0.6549
- Recall: 0.6403

## 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: 5e-05
- train_batch_size: 30
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.7851        | 1.0   | 22   | 1.7324          | 0.3381   | 0.2327 | 0.3338    | 0.3381 |
| 1.6204        | 2.0   | 44   | 1.6785          | 0.3165   | 0.2082 | 0.2941    | 0.3165 |
| 1.3964        | 3.0   | 66   | 1.4346          | 0.5036   | 0.4611 | 0.4823    | 0.5036 |
| 0.9218        | 4.0   | 88   | 1.2695          | 0.5612   | 0.5181 | 0.4952    | 0.5612 |
| 0.4872        | 5.0   | 110  | 1.3801          | 0.6043   | 0.5794 | 0.5676    | 0.6043 |
| 0.2341        | 6.0   | 132  | 1.3891          | 0.6115   | 0.5997 | 0.5910    | 0.6115 |
| 0.123         | 7.0   | 154  | 1.4263          | 0.6259   | 0.6070 | 0.6180    | 0.6259 |
| 0.0737        | 8.0   | 176  | 1.6080          | 0.6331   | 0.6214 | 0.6336    | 0.6331 |
| 0.038         | 9.0   | 198  | 1.6996          | 0.6187   | 0.6075 | 0.6016    | 0.6187 |
| 0.0278        | 10.0  | 220  | 1.8417          | 0.6475   | 0.6446 | 0.6595    | 0.6475 |
| 0.0142        | 11.0  | 242  | 1.7940          | 0.6547   | 0.6543 | 0.6737    | 0.6547 |
| 0.0085        | 12.0  | 264  | 1.9102          | 0.6187   | 0.6142 | 0.6273    | 0.6187 |
| 0.0035        | 13.0  | 286  | 1.9572          | 0.6403   | 0.6414 | 0.6647    | 0.6403 |
| 0.0024        | 14.0  | 308  | 1.9346          | 0.6475   | 0.6441 | 0.6568    | 0.6475 |
| 0.0021        | 15.0  | 330  | 1.9751          | 0.6475   | 0.6436 | 0.6606    | 0.6475 |
| 0.0017        | 16.0  | 352  | 2.0226          | 0.6547   | 0.6519 | 0.6687    | 0.6547 |
| 0.0016        | 17.0  | 374  | 2.0257          | 0.6475   | 0.6458 | 0.6629    | 0.6475 |
| 0.0015        | 18.0  | 396  | 2.0326          | 0.6403   | 0.6388 | 0.6549    | 0.6403 |
| 0.0014        | 19.0  | 418  | 2.0369          | 0.6403   | 0.6388 | 0.6549    | 0.6403 |
| 0.0014        | 20.0  | 440  | 2.0387          | 0.6403   | 0.6388 | 0.6549    | 0.6403 |


### Framework versions

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