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results
This model is a fine-tuned version of Helsinki-NLP/opus-mt-de-en on the wmt16 dataset. It achieves the following results on the evaluation set:
- Loss: 1.3984
- Bleu-1: 0.8788
- Bleu-2: 0.8122
- Rouge-l: 0.6251
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu-1 | Bleu-2 | Rouge-l |
|---|---|---|---|---|---|---|
| 2.2098 | 1.0 | 995 | 2.1014 | 0.8223 | 0.7409 | 0.5191 |
| 1.7011 | 2.0 | 1990 | 2.1251 | 0.8195 | 0.7382 | 0.517 |
| 1.3455 | 3.0 | 2985 | 2.1688 | 0.8204 | 0.7387 | 0.5154 |
| 1.1516 | 4.0 | 3980 | 2.2028 | 0.8201 | 0.7383 | 0.5151 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.2
