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Whisper Small Jyutping without Tones (Trained on almost all open source Cantonese datasets)

This model is a fine-tuned version of openai/whisper-small on the Common Voice 14.0 Yue & zh-HK + MDCC dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0560
  • Wer: 5.5162

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: 16
  • 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

Training results

Training Loss Epoch Step Validation Loss Wer
0.0655 0.07 1000 0.0948 8.6022
0.0577 0.13 2000 0.0747 6.9833
0.0496 0.2 3000 0.0627 6.8633
0.0558 0.27 4000 0.0560 5.5162

Framework versions

  • Transformers 4.34.0.dev0
  • Pytorch 2.0.1
  • Datasets 2.14.5
  • Tokenizers 0.13.3
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