Models GEC spanish
Collection
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mbart-large-50-GEC-spanish-LORA-cowsl2h
This model is a fine-tuned version of facebook/mbart-large-50 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 8.1436
- Gleu: 0.3894
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: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Gleu |
|---|---|---|---|---|
| 9.2131 | 1.0 | 388 | 8.1384 | 0.4301 |
| 8.1633 | 2.0 | 776 | 8.1093 | 0.5478 |
| 8.1815 | 3.0 | 1164 | 8.1496 | 0.3411 |
| 8.1746 | 4.0 | 1552 | 8.1436 | 0.3894 |
Framework versions
- PEFT 0.18.1
- Transformers 5.0.0
- Pytorch 2.7.0+cu126
- Datasets 4.8.5
- Tokenizers 0.22.2
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Base model
facebook/mbart-large-50
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Ro551/mbart-large-50-GEC-spanish-LORA-cowsl2h", device_map="auto")