Whisper Small Uz - Azamat Urinboyev
This model is a fine-tuned version of openai/whisper-small on the Common Voice 8.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3743
- Wer: 29.1593
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 |
|---|---|---|---|---|
| 0.3146 | 1.3514 | 1000 | 0.4122 | 35.3898 |
| 0.1332 | 2.7027 | 2000 | 0.3529 | 29.7356 |
| 0.0256 | 4.0541 | 3000 | 0.3658 | 29.2881 |
| 0.0134 | 5.4054 | 4000 | 0.3743 | 29.1593 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1
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