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mbart-neutralization
carmengoar/mbart-neutralization
mbart-neutralization is a machine learning model from carmengoar. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Feb 24, 2026
- Updated
- Mar 8, 2026
- SHA
- da103d44
Base models
Model card
From the Hugging Face model README
<!-- 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 t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1563
- Bleu: 53.022
- Gen Len: 18.5417
Model description
This model has been created as part of an activity for the course "Traducción Automática", at the Máster de Procesamiento del Lenguaje y Aplicaciones de la Inteligencia Artificial a la Lingüística (Universidad de La Rioja).
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 | 0.2031 | 53.022 | 18.5417 |
| 0.2886 | 2.0 | 880 | 0.1563 | 53.022 | 18.5417 |
Framework versions
- Transformers 4.51.2
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.21.4
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Languages
- es
- Created
- Feb 24, 2026
- Updated
- Mar 8, 2026