| --- |
| 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-baseline-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-baseline-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: 1.2295 |
| - Accuracy: 0.8864 |
| - F1: 0.5455 |
| - Precision: 0.6923 |
| - Recall: 0.45 |
|
|
| ## 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: 150 |
| - 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
| | 0.8186 | 1.0 | 77 | 0.6756 | 0.8485 | 0.0 | 0.0 | 0.0 | |
| | 0.6938 | 2.0 | 154 | 0.6323 | 0.8636 | 0.1818 | 1.0 | 0.1 | |
| | 0.6306 | 3.0 | 231 | 0.5534 | 0.8939 | 0.5625 | 0.75 | 0.45 | |
| | 0.5361 | 4.0 | 308 | 0.5799 | 0.7045 | 0.4658 | 0.3208 | 0.85 | |
| | 0.3683 | 5.0 | 385 | 0.9161 | 0.8712 | 0.5405 | 0.5882 | 0.5 | |
| | 0.3116 | 6.0 | 462 | 1.2295 | 0.8864 | 0.5455 | 0.6923 | 0.45 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.57.3 |
| - Pytorch 2.9.1+cu128 |
| - Datasets 4.4.1 |
| - Tokenizers 0.22.1 |
| |
