Whisper Small Uz - Aslon Khamidov
This model is a fine-tuned version of openai/whisper-small on the Common Voice 16.1 dataset and converted to ctranslate2 type model.
Model description
Automatic Speech Recognition - Whisper
Intended uses & limitations
For speech to text
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: 2000
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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