Whisper Medium KK - Kazakh - Fleurs - Common Voice
This model is a fine-tuned version of nocturneFlow/whisper-medium-ft on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0778
- Wer: 10.2803
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1487 | 0.2173 | 1000 | 0.1408 | 17.6987 |
| 0.1137 | 0.4347 | 2000 | 0.1059 | 13.7526 |
| 0.092 | 0.6520 | 3000 | 0.0924 | 12.0276 |
| 0.0814 | 0.8693 | 4000 | 0.0814 | 10.6566 |
| 0.047 | 1.0865 | 5000 | 0.0778 | 10.2803 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu118
- Datasets 3.6.0
- Tokenizers 0.21.0
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