---
library_name: transformers
base_model: cardiffnlp/twitter-xlm-roberta-base-hate-spanish
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: MultiPRIDE-DualEncoder-LPFT-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. -->

# MultiPRIDE-DualEncoder-LPFT-es

This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base-hate-spanish](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-hate-spanish) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6249
- Accuracy: 0.8030
- F1: 0.4583
- Precision: 0.3929
- Recall: 0.55

## 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: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6889        | 1.0   | 77   | 0.6662          | 0.6667   | 0.3333 | 0.2391    | 0.55   |
| 0.6354        | 2.0   | 154  | 0.6400          | 0.7879   | 0.2632 | 0.2778    | 0.25   |
| 0.6131        | 3.0   | 231  | 0.6525          | 0.8409   | 0.2759 | 0.4444    | 0.2    |
| 0.5588        | 4.0   | 308  | 0.6100          | 0.8030   | 0.4091 | 0.375     | 0.45   |
| 0.4774        | 5.0   | 385  | 0.6230          | 0.8106   | 0.4444 | 0.4       | 0.5    |
| 0.4569        | 6.0   | 462  | 0.6283          | 0.8106   | 0.4681 | 0.4074    | 0.55   |
| 0.4519        | 7.0   | 539  | 0.6239          | 0.8030   | 0.4583 | 0.3929    | 0.55   |
| 0.4671        | 8.0   | 616  | 0.6284          | 0.8106   | 0.4681 | 0.4074    | 0.55   |
| 0.4231        | 9.0   | 693  | 0.6249          | 0.8030   | 0.4583 | 0.3929    | 0.55   |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.9.1+cu128
- Datasets 4.4.1
- Tokenizers 0.22.1