---
license: apache-2.0
base_model: VerificadoProfesional/SaBERT-Spanish-Sentiment-Analysis
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: my-model-Sabert-Sentimento
  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-Sabert-Sentimento

This model is a fine-tuned version of [VerificadoProfesional/SaBERT-Spanish-Sentiment-Analysis](https://huggingface.co/VerificadoProfesional/SaBERT-Spanish-Sentiment-Analysis) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3425
- Accuracy: 0.9355
- F1: 0.9276
- Precision: 0.9253
- Recall: 0.9355

## 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: 0.0002
- train_batch_size: 30
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4095        | 1.0   | 25   | 0.2597          | 0.9355   | 0.9276 | 0.9253    | 0.9355 |
| 0.1831        | 2.0   | 50   | 0.3267          | 0.9226   | 0.9024 | 0.9223    | 0.9226 |
| 0.138         | 3.0   | 75   | 0.3843          | 0.9290   | 0.9125 | 0.9278    | 0.9290 |
| 0.0776        | 4.0   | 100  | 0.3418          | 0.9290   | 0.9240 | 0.9199    | 0.9290 |
| 0.0561        | 5.0   | 125  | 0.3425          | 0.9355   | 0.9276 | 0.9253    | 0.9355 |


### Framework versions

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