---
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
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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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0108
- Bleu: 98.1545
- Gen Len: 18.8229

## Model description

Disclaimer: this is part of a practical excerise carried out as part of the University course "Machine Traslation" of the Master's Degree in Language Processing and Applied AI to Linguistcs of Universidad de La Rioja.
This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0108
- Bleu: 98.1545
- Gen Len: 18.8229

## Intended uses & limitations

More information needed

## 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  | 0.0220          | 98.1628 | 18.8229 |
| 0.2273        | 2.0   | 880  | 0.0108          | 98.1545 | 18.8229 |


### Framework versions

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