| | --- |
| | 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 |
| | |
