opus-mt-en-ru-finetuned-en-to-ru
This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-ru on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7682
- Bleu: 14.6112
- Gen Len: 7.202
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: 16
- eval_batch_size: 16
- 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 |
---|---|---|---|---|---|
2.3198 | 1.0 | 4956 | 2.1261 | 9.5339 | 6.7709 |
1.9732 | 2.0 | 9912 | 1.9639 | 10.4715 | 7.1254 |
1.7127 | 3.0 | 14868 | 1.8780 | 11.6128 | 7.1106 |
1.5614 | 4.0 | 19824 | 1.8367 | 12.8389 | 7.0468 |
1.4276 | 5.0 | 24780 | 1.8040 | 13.7423 | 7.0403 |
1.3096 | 6.0 | 29736 | 1.7820 | 14.1469 | 7.0555 |
1.2381 | 7.0 | 34692 | 1.7761 | 13.9987 | 7.2225 |
1.1784 | 8.0 | 39648 | 1.7725 | 14.4675 | 7.1799 |
1.1376 | 9.0 | 44604 | 1.7692 | 14.4937 | 7.1957 |
1.0862 | 10.0 | 49560 | 1.7682 | 14.6112 | 7.202 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.17.0
- Tokenizers 0.10.3
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