opus-mt-es-en-GEC-spanish-cowsl2h-exp
This model is a fine-tuned version of Helsinki-NLP/opus-mt-es-en on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1718
- Gleu: 0.4337
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Gleu |
|---|---|---|---|---|
| 2.9951 | 1.0 | 194 | 0.3505 | 0.2378 |
| 1.2865 | 2.0 | 388 | 0.2692 | 0.3163 |
| 0.7821 | 3.0 | 582 | 0.2054 | 0.3899 |
| 0.3901 | 4.0 | 776 | 0.1718 | 0.4337 |
Framework versions
- Transformers 5.5.1
- Pytorch 2.11.0+cu128
- Datasets 4.8.5
- Tokenizers 0.22.2