Whisper Small Uz
This model is a fine-tuned version of openai/whisper-small on the Mozilla Common Voice (Uzbek) dataset. It achieves the following results on the evaluation set:
- Loss: 0.7149
- Wer Ortho: 60.6736
- Wer: 50.4066
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_FUSED 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: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.6628 | 0.8 | 500 | 0.7149 | 60.6736 | 50.4066 |
Framework versions
- Transformers 5.13.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
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Evaluation results
- Wer on Mozilla Common Voice (Uzbek)self-reported50.407