---
library_name: transformers
license: mit
base_model: facebook/mbart-large-50
tags:
- simplification
- generated_from_trainer
metrics:
- bleu
model-index:
- name: mbart-translation-DDHH
  results: []
---

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# mbart-translation-DDHH

This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) trained on a parallel English–Spanish corpus of the Universal Declaration of Human Rights.
It achieves the following results on the evaluation set:
- Loss: 3.6758
- Bleu: 33.4177
- Gen Len: 25.95

## Model description

This model is based on mBART-50, a multilingual sequence-to-sequence model, and has been fine-tuned to improve the quality of translations between English and Spanish for the specific domain of legal/human-rights text. It is designed to produce fluent and accurate sentence-level translations that maintain the formal tone and legal register of the source material.

## Intended uses & limitations

Intended use: Automatic English↔Spanish translation of legal or policy-oriented texts, especially those similar in style to the Universal Declaration of Human Rights.
Limitations: specialized in one specific domain (the Universal Declaration of Human Rights) and may not generalize well to informal or highly technical text outside this domain.

## Training and evaluation data

The model was fine-tuned on a parallel corpus of the Universal Declaration of Human Rights in English and Spanish. The training set included sentence-aligned text segments extracted from publicly available translations of the declaration.

## Training procedure

The fine-tuning was conducted on a single GPU using the transformers library from Hugging Face.

### 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   | 10   | 3.8374          | 28.2511 | 23.65   |
| No log        | 2.0   | 20   | 3.6758          | 33.4177 | 25.95   |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1