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