---
library_name: transformers
license: mit
base_model: facebook/mbart-large-50
tags:
- simplification
- generated_from_trainer
metrics:
- bleu
model-index:
- name: mbart-neutralization
  results: []
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 the "hackathon-pln-es/neutral-es" dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0323
- Bleu: 98.8828
- Gen Len: 18.6771

## Model description

This model translates from “standard” to neutral Spanish. For example, it replaces gender markers in plurals with neuter constructions.


## 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  | 0.0149          | 98.9442 | 18.5938 |
| 0.2266        | 2.0   | 880  | 0.0323          | 98.8828 | 18.6771 |


### Framework versions

- Transformers 4.50.1
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1