helsinki-neutralization
This model is a fine-tuned version of Helsinki-NLP/opus-mt-es-es on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0638
- Bleu: 97.3609
- Gen Len: 15.8854
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: 5.6e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| No log | 1.0 | 440 | 0.0788 | 93.9304 | 15.7812 |
| 0.9400 | 2.0 | 880 | 0.0638 | 97.3609 | 15.8854 |
Framework versions
- Transformers 5.2.0
- Pytorch 2.10.0+cpu
- Datasets 4.6.0
- Tokenizers 0.22.2
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Model tree for canl0we/helsinki-neutralization
Base model
Helsinki-NLP/opus-mt-es-es