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---
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-MainStage-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-MainStage-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: 0.5697
- Accuracy: 0.8030
- F1: 0.48
- Precision: 0.4
- Recall: 0.6
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6627 | 1.0 | 77 | 0.6301 | 0.7879 | 0.3 | 0.3 | 0.3 |
| 0.5988 | 2.0 | 154 | 0.6037 | 0.7424 | 0.2609 | 0.2308 | 0.3 |
| 0.5895 | 3.0 | 231 | 0.5760 | 0.7879 | 0.3333 | 0.3182 | 0.35 |
| 0.5471 | 4.0 | 308 | 0.5450 | 0.7879 | 0.4615 | 0.375 | 0.6 |
| 0.4608 | 5.0 | 385 | 0.5414 | 0.7727 | 0.4444 | 0.3529 | 0.6 |
| 0.4488 | 6.0 | 462 | 0.5611 | 0.8030 | 0.48 | 0.4 | 0.6 |
| 0.4577 | 7.0 | 539 | 0.5658 | 0.8106 | 0.4898 | 0.4138 | 0.6 |
| 0.4569 | 8.0 | 616 | 0.5713 | 0.8182 | 0.5 | 0.4286 | 0.6 |
| 0.4127 | 9.0 | 693 | 0.5705 | 0.8030 | 0.48 | 0.4 | 0.6 |
| 0.4133 | 10.0 | 770 | 0.5697 | 0.8030 | 0.48 | 0.4 | 0.6 |
### Framework versions
- Transformers 4.57.3
- Pytorch 2.9.1+cu128
- Datasets 4.4.1
- Tokenizers 0.22.1
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