Whisper Small uz common voice
This model is a fine-tuned on the Common Voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.4867
- Wer: 44.1679
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1500
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.7832 | 0.13 | 500 | 0.7033 | 58.2757 |
0.6095 | 0.27 | 1000 | 0.5239 | 46.5073 |
0.5093 | 0.4 | 1500 | 0.4867 | 44.1679 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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