Whisper whisper-large-v3-turbo tsn
This model is a fine-tuned version of openai/whisper-large-v3-turbo on the dsfsi-anv/za-african-next-voices dataset. It achieves the following results on the evaluation set:
- Loss: 0.1287
- Wer: 16.8840
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: 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: constant_with_warmup
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2741 | 0.2 | 200 | 0.2627 | 18.7700 |
| 0.2048 | 0.4 | 400 | 0.1843 | 14.6258 |
| 0.22 | 0.6 | 600 | 0.1821 | 12.5586 |
| 0.1919 | 0.8 | 800 | 0.1386 | 10.1534 |
| 0.162 | 1.0 | 1000 | 0.1287 | 16.8840 |
Framework versions
- Transformers 4.52.0
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.4