---
base_model: MMG/mlm-spanish-roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-finetuned-intention-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-intention-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: 1.9097
- Accuracy: 0.6918
- Precision: 0.6953
- Recall: 0.6918
- F1: 0.6848

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.2985        | 1.0   | 102  | 1.7435          | 0.4970   | 0.4378    | 0.4970 | 0.4215 |
| 1.3399        | 2.0   | 204  | 1.4205          | 0.5828   | 0.5872    | 0.5828 | 0.5624 |
| 0.8893        | 3.0   | 306  | 1.2699          | 0.6393   | 0.6276    | 0.6393 | 0.6192 |
| 0.5691        | 4.0   | 408  | 1.3327          | 0.6515   | 0.6604    | 0.6515 | 0.6417 |
| 0.3837        | 5.0   | 510  | 1.3836          | 0.6592   | 0.6710    | 0.6592 | 0.6528 |
| 0.2543        | 6.0   | 612  | 1.4253          | 0.6641   | 0.6703    | 0.6641 | 0.6528 |
| 0.1669        | 7.0   | 714  | 1.5317          | 0.6650   | 0.6795    | 0.6650 | 0.6546 |
| 0.1139        | 8.0   | 816  | 1.5939          | 0.6725   | 0.6754    | 0.6725 | 0.6615 |
| 0.0805        | 9.0   | 918  | 1.6987          | 0.6594   | 0.6696    | 0.6594 | 0.6518 |
| 0.0578        | 10.0  | 1020 | 1.6960          | 0.6793   | 0.6782    | 0.6793 | 0.6690 |
| 0.0374        | 11.0  | 1122 | 1.7590          | 0.6824   | 0.6877    | 0.6824 | 0.6729 |
| 0.03          | 12.0  | 1224 | 1.7425          | 0.6842   | 0.6859    | 0.6842 | 0.6785 |
| 0.0183        | 13.0  | 1326 | 1.8165          | 0.6830   | 0.6846    | 0.6830 | 0.6774 |
| 0.0152        | 14.0  | 1428 | 1.8348          | 0.6866   | 0.6927    | 0.6866 | 0.6799 |
| 0.0109        | 15.0  | 1530 | 1.8562          | 0.6940   | 0.6967    | 0.6940 | 0.6855 |
| 0.0097        | 16.0  | 1632 | 1.8766          | 0.6889   | 0.6947    | 0.6889 | 0.6833 |
| 0.0073        | 17.0  | 1734 | 1.8745          | 0.6920   | 0.6948    | 0.6920 | 0.6851 |
| 0.0062        | 18.0  | 1836 | 1.8944          | 0.6895   | 0.6919    | 0.6895 | 0.6825 |
| 0.0057        | 19.0  | 1938 | 1.9103          | 0.6936   | 0.6984    | 0.6936 | 0.6867 |
| 0.0052        | 20.0  | 2040 | 1.9097          | 0.6918   | 0.6953    | 0.6918 | 0.6848 |


### Framework versions

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