Whisper Swahili Medium
This model is a fine-tuned version of openai/whisper-medium on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3519
- Wer: 25.2615
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 OptimizerNames.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: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3595 | 0.4342 | 1000 | 0.4586 | 31.5976 |
| 0.3001 | 0.8684 | 2000 | 0.3794 | 27.8295 |
| 0.1451 | 1.3026 | 3000 | 0.3701 | 26.1972 |
| 0.1469 | 1.7369 | 4000 | 0.3519 | 25.2615 |
Framework versions
- Transformers 4.46.0.dev0
- Pytorch 2.1.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
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Base model
openai/whisper-medium