whisper-large-v3-turbo-darija-st
This model is a fine-tuned version of openai/whisper-large-v3-turbo on the Darija-C dataset. It achieves the following results on the evaluation set:
- Loss: 0.4467
- Bleu: 0.1543
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: 500
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu |
|---|---|---|---|---|
| 9.4513 | 12.5 | 50 | 7.2648 | 0.0 |
| 6.3191 | 25.0 | 100 | 5.6246 | 0.0 |
| 5.3703 | 37.5 | 150 | 5.0543 | 0.0 |
| 4.8443 | 50.0 | 200 | 4.4717 | 0.0 |
| 4.1997 | 62.5 | 250 | 3.8060 | 0.0 |
| 3.4159 | 75.0 | 300 | 3.0214 | 0.0 |
| 2.6566 | 87.5 | 350 | 2.3394 | 0.0000 |
| 2.1582 | 100.0 | 400 | 2.0106 | 0.0000 |
| 1.902 | 112.5 | 450 | 1.8156 | 0.0016 |
| 1.7201 | 125.0 | 500 | 1.5723 | 0.0000 |
| 1.4377 | 137.5 | 550 | 1.2928 | 0.0044 |
| 1.1887 | 150.0 | 600 | 1.0744 | 0.0038 |
| 0.9863 | 162.5 | 650 | 0.9181 | 0.0311 |
| 0.8339 | 175.0 | 700 | 0.7674 | 0.1133 |
| 0.7106 | 187.5 | 750 | 0.6533 | 0.1300 |
| 0.6131 | 200.0 | 800 | 0.5704 | 0.1339 |
| 0.5454 | 212.5 | 850 | 0.5155 | 0.1336 |
| 0.4952 | 225.0 | 900 | 0.4789 | 0.1210 |
| 0.4647 | 237.5 | 950 | 0.4567 | 0.1969 |
| 0.4461 | 250.0 | 1000 | 0.4467 | 0.1543 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 2.19.2
- Tokenizers 0.21.0