Finetuned Whisper large-v3 for darija speech translation
This model is a fine-tuned version of openai/whisper-large-v3 on the Darija-C dataset. It achieves the following results on the evaluation set:
- Loss: 0.0000
- Bleu: 0.7440
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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu |
|---|---|---|---|---|
| 3.0209 | 0.8333 | 50 | 1.5160 | 0.0385 |
| 1.4379 | 1.6667 | 100 | 0.7678 | 0.1508 |
| 0.8536 | 2.5 | 150 | 0.3769 | 0.2512 |
| 0.4203 | 3.3333 | 200 | 0.2265 | 0.4909 |
| 0.3585 | 4.1667 | 250 | 0.0945 | 0.5903 |
| 0.1791 | 5.0 | 300 | 0.0498 | 0.6521 |
| 0.0894 | 5.8333 | 350 | 0.0388 | 0.6798 |
| 0.0827 | 6.6667 | 400 | 0.0185 | 0.7029 |
| 0.0119 | 7.5 | 450 | 0.0266 | 0.7213 |
| 0.0255 | 8.3333 | 500 | 0.0232 | 0.7021 |
| 0.0296 | 9.1667 | 550 | 0.0002 | 0.7440 |
| 0.0082 | 10.0 | 600 | 0.0001 | 0.7440 |
| 0.0001 | 10.8333 | 650 | 0.0001 | 0.7440 |
| 0.0001 | 11.6667 | 700 | 0.0000 | 0.7440 |
| 0.0 | 12.5 | 750 | 0.0000 | 0.7440 |
| 0.0 | 13.3333 | 800 | 0.0000 | 0.7440 |
| 0.0 | 14.1667 | 850 | 0.0000 | 0.7440 |
| 0.0 | 15.0 | 900 | 0.0000 | 0.7440 |
| 0.0 | 15.8333 | 950 | 0.0000 | 0.7440 |
| 0.0 | 16.6667 | 1000 | 0.0000 | 0.7440 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 2.19.2
- Tokenizers 0.21.0