---
library_name: transformers
license: mit
base_model: facebook/mbart-large-50
tags:
- simplification
- generated_from_trainer
metrics:
- bleu
model-index:
- name: mbart-neutralizacion-es
  results: []
datasets:
- somosnlp-hackathon-2022/neutral-es
---

# mbart-neutralizacion-es

This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on dataset somosnlp-hackathon-2022/neutral-es.
It achieves the following results on the evaluation set:
- Loss: 0.0104
- Bleu: 99.0106
- Gen Len: 18.6146

## Model description

Model to neutralize gendered text.

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 10
- eval_batch_size: 10
- 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| No log        | 1.0   | 352  | 0.0304          | 97.1712 | 18.5729 |
| 1.6026        | 2.0   | 704  | 0.0121          | 98.6521 | 18.5729 |
| 0.0232        | 3.0   | 1056 | 0.0104          | 99.0106 | 18.6146 |


### Framework versions

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