Whisper Small Uz - Doniyor Halilov
This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.0147
- Wer: 54.7492
Model description
More information needed
Intended uses & limitations
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Training and evaluation data
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Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 200
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.612 | 0.0132 | 100 | 1.2551 | 69.5533 |
| 1.1271 | 0.0264 | 200 | 1.0147 | 54.7492 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1+cu118
- Datasets 3.0.1
- Tokenizers 0.20.1
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