Models GEC spanish
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opus-mt-es-en-GEC-spanish-cowsl2h
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: 0.1180
- Gleu: 0.4730
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: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Gleu |
|---|---|---|---|---|
| 0.3908 | 1.0 | 388 | 0.1504 | 0.3852 |
| 0.2316 | 2.0 | 776 | 0.1253 | 0.4443 |
| 0.1546 | 3.0 | 1164 | 0.1192 | 0.4662 |
| 0.1141 | 4.0 | 1552 | 0.1180 | 0.4730 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.7.0+cu126
- Datasets 4.8.5
- Tokenizers 0.22.2
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Base model
Helsinki-NLP/opus-mt-es-en
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Ro551/opus-mt-es-en-GEC-spanish-cowsl2h") model = AutoModelForSeq2SeqLM.from_pretrained("Ro551/opus-mt-es-en-GEC-spanish-cowsl2h", device_map="auto")