---
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: 3.1711
- Accuracy: 0.4903
- F1: 0.4767
- Precision: 0.5366
- Recall: 0.4903

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.8349        | 1.0   | 25   | 1.7703          | 0.3032   | 0.2608 | 0.2991    | 0.3032 |
| 1.7709        | 2.0   | 50   | 1.7153          | 0.3355   | 0.2347 | 0.2079    | 0.3355 |
| 1.7315        | 3.0   | 75   | 1.6515          | 0.3613   | 0.2934 | 0.2937    | 0.3613 |
| 1.596         | 4.0   | 100  | 1.6332          | 0.3871   | 0.3405 | 0.3123    | 0.3871 |
| 1.3388        | 5.0   | 125  | 1.6449          | 0.4065   | 0.3298 | 0.2900    | 0.4065 |
| 1.0783        | 6.0   | 150  | 1.5722          | 0.4581   | 0.3797 | 0.3760    | 0.4581 |
| 0.8663        | 7.0   | 175  | 1.6593          | 0.3935   | 0.3563 | 0.3490    | 0.3935 |
| 0.6118        | 8.0   | 200  | 1.9177          | 0.4581   | 0.4481 | 0.4658    | 0.4581 |
| 0.4206        | 9.0   | 225  | 2.2944          | 0.4065   | 0.3920 | 0.4286    | 0.4065 |
| 0.3375        | 10.0  | 250  | 2.2870          | 0.4387   | 0.4359 | 0.4889    | 0.4387 |
| 0.2334        | 11.0  | 275  | 2.4912          | 0.4065   | 0.4015 | 0.4546    | 0.4065 |
| 0.1618        | 12.0  | 300  | 2.5429          | 0.4710   | 0.4499 | 0.5204    | 0.4710 |
| 0.1238        | 13.0  | 325  | 2.7109          | 0.4710   | 0.4458 | 0.5135    | 0.4710 |
| 0.0906        | 14.0  | 350  | 2.8377          | 0.4774   | 0.4594 | 0.5092    | 0.4774 |
| 0.071         | 15.0  | 375  | 3.0123          | 0.4839   | 0.4656 | 0.5461    | 0.4839 |
| 0.0498        | 16.0  | 400  | 3.0204          | 0.4710   | 0.4517 | 0.4959    | 0.4710 |
| 0.0416        | 17.0  | 425  | 3.0939          | 0.4839   | 0.4622 | 0.5107    | 0.4839 |
| 0.0281        | 18.0  | 450  | 3.0979          | 0.4903   | 0.4793 | 0.5281    | 0.4903 |
| 0.0226        | 19.0  | 475  | 3.1622          | 0.4839   | 0.4708 | 0.5202    | 0.4839 |
| 0.0185        | 20.0  | 500  | 3.1711          | 0.4903   | 0.4767 | 0.5366    | 0.4903 |


### Framework versions

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