---
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
---

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# 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