opus-mt-fr-de-new-finetuned-fr-to-wol
This model is a fine-tuned version of Helsinki-NLP/opus-mt-fr-de on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.4897
- Bleu: 5.5073
- Gen Len: 61.5873
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: 0.0003
- train_batch_size: 64
- eval_batch_size: 64
- 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 | 91 | 3.0424 | 0.4073 | 288.4603 |
No log | 2.0 | 182 | 2.6751 | 0.9893 | 166.5666 |
No log | 3.0 | 273 | 2.4795 | 3.1938 | 80.8081 |
No log | 4.0 | 364 | 2.3826 | 4.1209 | 73.1684 |
No log | 5.0 | 455 | 2.3629 | 4.858 | 63.6266 |
2.5384 | 6.0 | 546 | 2.3635 | 5.1207 | 66.588 |
2.5384 | 7.0 | 637 | 2.3929 | 5.3246 | 61.1974 |
2.5384 | 8.0 | 728 | 2.4382 | 5.5606 | 63.0014 |
2.5384 | 9.0 | 819 | 2.4625 | 5.3472 | 62.4086 |
2.5384 | 10.0 | 910 | 2.4897 | 5.5073 | 61.5873 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2
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Base model
Helsinki-NLP/opus-mt-fr-de