---
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-LGBT-Pretrain-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-LGBT-Pretrain-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: 1.4954
- Accuracy: 0.7652
- F1: 0.7862
- Precision: 0.8507
- Recall: 0.7308

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6914        | 1.0   | 77   | 0.6991          | 0.75     | 0.7898 | 0.7848    | 0.7949 |
| 0.495         | 2.0   | 154  | 0.5171          | 0.75     | 0.7898 | 0.7848    | 0.7949 |
| 0.3892        | 3.0   | 231  | 0.8120          | 0.7348   | 0.7482 | 0.8525    | 0.6667 |
| 0.2307        | 4.0   | 308  | 1.1109          | 0.7803   | 0.8079 | 0.8356    | 0.7821 |
| 0.2412        | 5.0   | 385  | 1.3397          | 0.7121   | 0.7246 | 0.8333    | 0.6410 |
| 0.1925        | 6.0   | 462  | 1.3379          | 0.7955   | 0.8402 | 0.7802    | 0.9103 |
| 0.0852        | 7.0   | 539  | 1.3290          | 0.7652   | 0.7891 | 0.8406    | 0.7436 |
| 0.0014        | 8.0   | 616  | 1.3692          | 0.7727   | 0.7973 | 0.8429    | 0.7564 |
| 0.028         | 9.0   | 693  | 1.4954          | 0.7652   | 0.7862 | 0.8507    | 0.7308 |


### Framework versions

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