metadata
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
mbart-neutralization
This model is a fine-tuned version of 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