---
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: 2.0081
- Accuracy: 0.5540
- F1: 0.5447
- Precision: 0.6083
- Recall: 0.5540

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.8057        | 1.0   | 22   | 1.6694          | 0.3094   | 0.1478 | 0.0971    | 0.3094 |
| 1.6881        | 2.0   | 44   | 1.5645          | 0.3741   | 0.2735 | 0.2381    | 0.3741 |
| 1.4559        | 3.0   | 66   | 1.3527          | 0.5612   | 0.4682 | 0.4308    | 0.5612 |
| 1.0349        | 4.0   | 88   | 1.2698          | 0.5108   | 0.4710 | 0.5251    | 0.5108 |
| 0.5922        | 5.0   | 110  | 1.3228          | 0.5396   | 0.5357 | 0.5761    | 0.5396 |
| 0.3388        | 6.0   | 132  | 1.3421          | 0.5324   | 0.5465 | 0.6025    | 0.5324 |
| 0.1581        | 7.0   | 154  | 1.6898          | 0.5396   | 0.5210 | 0.6214    | 0.5396 |
| 0.0756        | 8.0   | 176  | 1.5726          | 0.5971   | 0.5805 | 0.5852    | 0.5971 |
| 0.0485        | 9.0   | 198  | 1.6224          | 0.5971   | 0.6071 | 0.6341    | 0.5971 |
| 0.0238        | 10.0  | 220  | 1.9468          | 0.5683   | 0.5592 | 0.6588    | 0.5683 |
| 0.0111        | 11.0  | 242  | 1.8085          | 0.5540   | 0.5505 | 0.5994    | 0.5540 |
| 0.0043        | 12.0  | 264  | 1.7379          | 0.5755   | 0.5672 | 0.6076    | 0.5755 |
| 0.0029        | 13.0  | 286  | 1.9594          | 0.5612   | 0.5527 | 0.6202    | 0.5612 |
| 0.0024        | 14.0  | 308  | 2.0399          | 0.5683   | 0.5606 | 0.6429    | 0.5683 |
| 0.0021        | 15.0  | 330  | 1.9871          | 0.5540   | 0.5447 | 0.6083    | 0.5540 |
| 0.002         | 16.0  | 352  | 1.9870          | 0.5540   | 0.5447 | 0.6083    | 0.5540 |
| 0.0018        | 17.0  | 374  | 1.9927          | 0.5540   | 0.5447 | 0.6083    | 0.5540 |
| 0.0018        | 18.0  | 396  | 2.0027          | 0.5540   | 0.5447 | 0.6083    | 0.5540 |
| 0.0017        | 19.0  | 418  | 2.0077          | 0.5540   | 0.5447 | 0.6083    | 0.5540 |
| 0.0017        | 20.0  | 440  | 2.0081          | 0.5540   | 0.5447 | 0.6083    | 0.5540 |


### Framework versions

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