---
library_name: transformers
license: apache-2.0
base_model: Helsinki-NLP/opus-mt-es-en
tags:
- generated_from_trainer
model-index:
- name: opus-mt-es-en-GEC-spanish-synthetic
  results: []
---

<!-- 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. -->

# opus-mt-es-en-GEC-spanish-synthetic

This model is a fine-tuned version of [Helsinki-NLP/opus-mt-es-en](https://huggingface.co/Helsinki-NLP/opus-mt-es-en) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0312
- Gleu: 0.9111

## 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: 8.441362564622899e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: 0.09363965565984424
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Gleu   |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.1056        | 1.0   | 10826 | 0.0418          | 0.8889 |
| 0.0621        | 2.0   | 21652 | 0.0312          | 0.9111 |


### Framework versions

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