Whisper Small UZ - Bahriddin Mo'minov
This model is a fine-tuned version of openai/whisper-small on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3379
- Wer: 28.6925
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 |
|---|---|---|---|---|
| 0.5499 | 0.2641 | 1000 | 0.5142 | 39.8375 |
| 0.4419 | 0.5281 | 2000 | 0.4080 | 33.3644 |
| 0.3506 | 0.7922 | 3000 | 0.3544 | 29.7293 |
| 0.242 | 1.0562 | 4000 | 0.3379 | 28.6925 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.2.2+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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