---
license: apache-2.0
tags:
- generated_from_trainer
base_model: VerificadoProfesional/SaBERT-Spanish-Sentiment-Analysis
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: 0.0937
- Accuracy: 0.9742
- F1: 0.9091
- Precision: 0.9524
- Recall: 0.8696

## 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: 8
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.2992        | 1.0   | 91   | 0.1026          | 0.9484   | 0.7895 | 1.0       | 0.6522 |
| 0.1379        | 2.0   | 182  | 0.1494          | 0.9548   | 0.8293 | 0.9444    | 0.7391 |
| 0.0415        | 3.0   | 273  | 0.0744          | 0.9742   | 0.9091 | 0.9524    | 0.8696 |
| 0.0249        | 4.0   | 364  | 0.0761          | 0.9742   | 0.9091 | 0.9524    | 0.8696 |
| 0.0173        | 5.0   | 455  | 0.0937          | 0.9742   | 0.9091 | 0.9524    | 0.8696 |


### Framework versions

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