tatoeba-tok-fr
This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-fr on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3544
- Bleu: 23.4181
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu |
|---|---|---|---|---|
| 1.8608 | 1.0 | 1167 | 1.6433 | 13.4398 |
| 1.593 | 2.0 | 2334 | 1.5195 | 17.7658 |
| 1.4354 | 3.0 | 3501 | 1.4565 | 15.5366 |
| 1.3449 | 4.0 | 4668 | 1.4217 | 19.8814 |
| 1.2681 | 5.0 | 5835 | 1.4016 | 19.6534 |
| 1.2046 | 6.0 | 7002 | 1.3853 | 21.0562 |
| 1.1545 | 7.0 | 8169 | 1.3738 | 19.8606 |
| 1.1186 | 8.0 | 9336 | 1.3694 | 20.6401 |
| 1.0803 | 9.0 | 10503 | 1.3615 | 20.3338 |
| 1.0504 | 10.0 | 11670 | 1.3601 | 23.0924 |
| 1.021 | 11.0 | 12837 | 1.3570 | 22.4592 |
| 1.0041 | 12.0 | 14004 | 1.3547 | 22.5261 |
| 0.9865 | 13.0 | 15171 | 1.3546 | 23.0413 |
| 0.9706 | 14.0 | 16338 | 1.3544 | 23.1603 |
| 0.9658 | 15.0 | 17505 | 1.3548 | 23.7041 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.7.1+cu128
- Datasets 3.6.0
- Tokenizers 0.21.1
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Model tree for NetherQuartz/tatoeba-tok-fr
Base model
Helsinki-NLP/opus-mt-en-fr