Finetuned Whisper medium for darija speech translation
This model is a fine-tuned version of openai/whisper-medium 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: 16
- eval_batch_size: 8
- 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 |
|---|---|---|---|---|
| 2.3191 | 12.5 | 50 | 0.3022 | 0.4084 |
| 0.0359 | 25.0 | 100 | 0.0001 | 0.7440 |
| 0.0001 | 37.5 | 150 | 0.0001 | 0.7440 |
| 0.0001 | 50.0 | 200 | 0.0000 | 0.7440 |
| 0.0 | 62.5 | 250 | 0.0000 | 0.7440 |
| 0.0 | 75.0 | 300 | 0.0000 | 0.7440 |
| 0.0 | 87.5 | 350 | 0.0000 | 0.7440 |
| 0.0 | 100.0 | 400 | 0.0000 | 0.7440 |
| 0.0 | 112.5 | 450 | 0.0000 | 0.7440 |
| 0.0 | 125.0 | 500 | 0.0000 | 0.7440 |
| 0.0 | 137.5 | 550 | 0.0000 | 0.7440 |
| 0.0 | 150.0 | 600 | 0.0000 | 0.7440 |
| 0.0 | 162.5 | 650 | 0.0000 | 0.7440 |
| 0.0 | 175.0 | 700 | 0.0000 | 0.7440 |
| 0.0 | 187.5 | 750 | 0.0000 | 0.7440 |
| 0.0 | 200.0 | 800 | 0.0000 | 0.7440 |
| 0.0 | 212.5 | 850 | 0.0000 | 0.7440 |
| 0.0 | 225.0 | 900 | 0.0000 | 0.7440 |
| 0.0 | 237.5 | 950 | 0.0000 | 0.7440 |
| 0.0 | 250.0 | 1000 | 0.0000 | 0.7440 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 2.19.2
- Tokenizers 0.21.0