---
library_name: peft
license: apache-2.0
base_model: Helsinki-NLP/opus-mt-es-en
tags:
- base_model:adapter:Helsinki-NLP/opus-mt-es-en
- lora
- transformers
model-index:
- name: opus-mt-es-en-GEC-spanish-LORA-merged
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# opus-mt-es-en-GEC-spanish-LORA-merged

This model is a fine-tuned version of [Helsinki-NLP/opus-mt-es-en](https://huggingface.co/Helsinki-NLP/opus-mt-es-en) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0887
- Gleu: 0.7507

## 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: 0.0013223040248761528
- 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: 0.09857017609527079
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Gleu   |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.2414        | 1.0   | 11213 | 0.1116          | 0.7131 |
| 0.1471        | 2.0   | 22426 | 0.0887          | 0.7507 |


### Framework versions

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