---
base_model: pysentimiento/robertuito-sentiment-analysis
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: roBERTuito-Meta4Types-ft-ES
  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. -->

# roBERTuito-Meta4Types-ft-ES

This model is a fine-tuned version of [pysentimiento/robertuito-sentiment-analysis](https://huggingface.co/pysentimiento/robertuito-sentiment-analysis) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8547
- Roc Auc: 0.6496
- Hamming Loss: 0.1830
- F1 Score: 0.5653
- Accuracy: 0.5931
- Precision: 0.6214
- Recall: 0.5298

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Roc Auc | Hamming Loss | F1 Score | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------------:|:--------:|:--------:|:---------:|:------:|
| No log        | 1.0   | 204  | 0.5044          | 0.5     | 0.2026       | 0.2930   | 0.6176   | 0.9281    | 0.3333 |
| No log        | 2.0   | 408  | 0.4634          | 0.5717  | 0.1961       | 0.4829   | 0.6225   | 0.5819    | 0.4651 |
| 0.4697        | 3.0   | 612  | 0.4784          | 0.6173  | 0.1748       | 0.4993   | 0.6275   | 0.8438    | 0.4596 |
| 0.4697        | 4.0   | 816  | 0.6585          | 0.6129  | 0.2124       | 0.5351   | 0.5539   | 0.5456    | 0.5279 |
| 0.1464        | 5.0   | 1020 | 0.8070          | 0.5891  | 0.2010       | 0.4963   | 0.6078   | 0.5732    | 0.4703 |
| 0.1464        | 6.0   | 1224 | 0.7848          | 0.6094  | 0.1912       | 0.5294   | 0.5735   | 0.5916    | 0.4989 |
| 0.1464        | 7.0   | 1428 | 0.8547          | 0.6496  | 0.1830       | 0.5653   | 0.5931   | 0.6214    | 0.5298 |
| 0.0278        | 8.0   | 1632 | 0.9068          | 0.6152  | 0.1846       | 0.5396   | 0.5784   | 0.6114    | 0.5064 |
| 0.0278        | 9.0   | 1836 | 0.9251          | 0.6110  | 0.1961       | 0.5258   | 0.5588   | 0.5674    | 0.5023 |
| 0.0029        | 10.0  | 2040 | 0.9343          | 0.6146  | 0.1944       | 0.5276   | 0.5686   | 0.5751    | 0.5002 |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1