Whisper Small Cantonese - alycia
This model is a fine-tuned version of openai/whisper-small on the FLEURS dataset.
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: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 20
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.57.6
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.22.2
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openai/whisper-small