| | --- |
| | library_name: transformers |
| | license: mit |
| | base_model: facebook/mbart-large-50 |
| | tags: |
| | - simplification |
| | - generated_from_trainer |
| | metrics: |
| | - bleu |
| | model-index: |
| | - name: mbart-neutralization |
| | results: [] |
| | datasets: |
| | - somosnlp-hackathon-2022/neutral-es |
| | language: |
| | - es |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # mbart-neutralization |
| |
|
| | This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on the dataset "somosnlp-hackathon-2022/neutral-es". |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0416 |
| | - Bleu: 96.855 |
| | - Gen Len: 18.5417 |
| |
|
| | ## Model description |
| |
|
| | This model is designed to convert Spanish gendered text into inclusive language. It was developed as part of a Master’s degree project in Natural Language Processing (NLP). |
| |
|
| | ## Intended uses & limitations |
| |
|
| | The model was trained on a relatively small dataset, so its performance is limited and the results may not always be reliable. It is intended primarily for educational and experimental purposes. |
| |
|
| | ## Training and evaluation data |
| |
|
| | The model was trained with this dataset of Spanish Gender Neutralization: https://huggingface.co/datasets/somosnlp-hackathon-2022/neutral-es |
| |
|
| | ## Training procedure |
| |
|
| | ### Training hyperparameters |
| |
|
| | The following hyperparameters were used during training: |
| | - learning_rate: 5.6e-05 |
| | - train_batch_size: 1 |
| | - eval_batch_size: 1 |
| | - seed: 42 |
| | - optimizer: Use OptimizerNames.ADAFACTOR and the args are: |
| | No additional optimizer arguments |
| | - lr_scheduler_type: linear |
| | - num_epochs: 2 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |
| | |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:| |
| | | 0.0729 | 1.0 | 3513 | 0.0961 | 94.3227 | 18.3021 | |
| | | 0.0357 | 2.0 | 7026 | 0.0416 | 96.855 | 18.5417 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 5.2.0 |
| | - Pytorch 2.10.0+cu128 |
| | - Datasets 4.6.0 |
| | - Tokenizers 0.22.2 |
