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opus-mt-en-es-finetuned-es-to-maq
This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-es on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.7414
- Bleu: 6.663
- Gen Len: 94.437
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
---|---|---|---|---|---|
No log | 1.0 | 199 | 2.3505 | 2.7386 | 127.0327 |
No log | 2.0 | 398 | 2.0862 | 4.4403 | 97.3489 |
2.643 | 3.0 | 597 | 1.9576 | 5.2104 | 98.7116 |
2.643 | 4.0 | 796 | 1.8831 | 5.4016 | 98.4962 |
2.643 | 5.0 | 995 | 1.8320 | 5.6026 | 96.1826 |
1.9678 | 6.0 | 1194 | 1.7944 | 6.374 | 95.1398 |
1.9678 | 7.0 | 1393 | 1.7726 | 6.514 | 94.83 |
1.8281 | 8.0 | 1592 | 1.7551 | 6.7802 | 95.194 |
1.8281 | 9.0 | 1791 | 1.7451 | 6.7625 | 94.2091 |
1.8281 | 10.0 | 1990 | 1.7414 | 6.663 | 94.437 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3