---
library_name: peft
license: mit
base_model: facebook/mbart-large-50
tags:
- base_model:adapter:facebook/mbart-large-50
- lora
- transformers
model-index:
- name: mbart-large-50-GEC-spanish-LORA-cowsl2h
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# mbart-large-50-GEC-spanish-LORA-cowsl2h

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: 8.1098
- Gleu: 0.5515

## Model description

More information needed

## 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: 0.00044406688888615583
- train_batch_size: 16
- eval_batch_size: 16
- 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
- lr_scheduler_warmup_steps: 0.08309212265191754
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Gleu   |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 9.2875        | 1.0   | 388  | 8.1391          | 0.4431 |
| 8.1733        | 2.0   | 776  | 8.1141          | 0.5315 |
| 8.1488        | 3.0   | 1164 | 8.1098          | 0.5515 |


### Framework versions

- PEFT 0.18.1
- Transformers 5.0.0
- Pytorch 2.7.0+cu126
- Datasets 4.8.5
- Tokenizers 0.22.2