Whisper_Small_swahili_normal
This model is a fine-tuned version of openai/whisper-small on the Common Voice 13 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0724
- Wer Ortho: 5.5083
- Wer: 5.5068
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: 16
- 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: 50
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.1028 | 1.1220 | 500 | 0.1930 | 18.2956 | 18.2829 |
| 0.0067 | 3.116 | 1000 | 0.0871 | 7.6330 | 7.6218 |
| 0.0026 | 5.11 | 1500 | 0.0715 | 6.2008 | 6.2040 |
| 0.0007 | 7.104 | 2000 | 0.0724 | 5.5083 | 5.5068 |
Framework versions
- Transformers 4.50.2
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1