---
base_model: MMG/mlm-spanish-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-finetuned-gesture-prediction-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. -->

# roberta-finetuned-gesture-prediction-es

This model is a fine-tuned version of [MMG/mlm-spanish-roberta-base](https://huggingface.co/MMG/mlm-spanish-roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7706
- Accuracy: 0.7223
- Precision: 0.7215
- Recall: 0.7223
- F1: 0.7156

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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 | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.8523        | 1.0   | 102  | 1.2237          | 0.6618   | 0.6205    | 0.6618 | 0.6316 |
| 1.0093        | 2.0   | 204  | 1.1357          | 0.6886   | 0.6715    | 0.6886 | 0.6663 |
| 0.6999        | 3.0   | 306  | 1.1758          | 0.6884   | 0.7008    | 0.6884 | 0.6763 |
| 0.4872        | 4.0   | 408  | 1.1398          | 0.6955   | 0.6982    | 0.6955 | 0.6839 |
| 0.3198        | 5.0   | 510  | 1.2017          | 0.7096   | 0.7112    | 0.7096 | 0.7059 |
| 0.2414        | 6.0   | 612  | 1.2819          | 0.7152   | 0.7101    | 0.7152 | 0.7049 |
| 0.1676        | 7.0   | 714  | 1.3279          | 0.7299   | 0.7272    | 0.7299 | 0.7221 |
| 0.1245        | 8.0   | 816  | 1.4593          | 0.7098   | 0.7078    | 0.7098 | 0.7011 |
| 0.0843        | 9.0   | 918  | 1.5682          | 0.7134   | 0.7131    | 0.7134 | 0.7063 |
| 0.0636        | 10.0  | 1020 | 1.5447          | 0.7195   | 0.7161    | 0.7195 | 0.7128 |
| 0.0464        | 11.0  | 1122 | 1.6686          | 0.7118   | 0.7164    | 0.7118 | 0.7050 |
| 0.0367        | 12.0  | 1224 | 1.6438          | 0.7251   | 0.7252    | 0.7251 | 0.7181 |
| 0.0292        | 13.0  | 1326 | 1.6803          | 0.7232   | 0.7199    | 0.7232 | 0.7170 |
| 0.0227        | 14.0  | 1428 | 1.6852          | 0.7217   | 0.7193    | 0.7217 | 0.7157 |
| 0.0155        | 15.0  | 1530 | 1.7753          | 0.7219   | 0.7245    | 0.7219 | 0.7156 |
| 0.0123        | 16.0  | 1632 | 1.7875          | 0.7157   | 0.7149    | 0.7157 | 0.7085 |
| 0.0102        | 17.0  | 1734 | 1.7649          | 0.7159   | 0.7148    | 0.7159 | 0.7095 |
| 0.0076        | 18.0  | 1836 | 1.7740          | 0.7204   | 0.7201    | 0.7204 | 0.7141 |
| 0.0074        | 19.0  | 1938 | 1.7674          | 0.7244   | 0.7235    | 0.7244 | 0.7177 |
| 0.0061        | 20.0  | 2040 | 1.7706          | 0.7223   | 0.7215    | 0.7223 | 0.7156 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0