---
library_name: transformers
license: mit
base_model: facebook/mbart-large-50
tags:
- simplification
- generated_from_trainer
metrics:
- bleu
model-index:
- name: mbart-neutralization
  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. -->

# mbart-neutralization

This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on the dataset [Spanish Gender Neutralization
dataset](https://huggingface.co/datasets/hackathon-pln-es/neutral-es).
It achieves the following results on the evaluation set:
- Loss: 0.0117
- Bleu: 96.8831
- Gen Len: 22.9479

## Model description

This model intends to translate sentences from current Spanish to neutralised Spanish.

## Intended uses & limitations

This model has been created as an in-class exercice, so the coverage of it can be very limited.

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| No log        | 1.0   | 440  | 0.0212          | 97.3896 | 18.7604 |
| 0.2286        | 2.0   | 880  | 0.0117          | 96.8831 | 22.9479 |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0