Whisper Base Bisyllabic Jyutping

This model is a fine-tuned version of openai/whisper-base on the AlienKevin/cantone dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3613
  • Wer: 41.25

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: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 400
  • training_steps: 2400

Training results

Training Loss Epoch Step Validation Loss Wer
0.1093 0.08 400 0.3231 51.0417
0.0389 0.15 800 0.2922 40.4861
0.0237 0.23 1200 0.3020 37.7778
0.0131 0.3 1600 0.3561 42.7083
0.01 0.38 2000 0.3817 44.6528
0.0095 0.46 2400 0.3613 41.25

Framework versions

  • Transformers 4.38.0.dev0
  • Pytorch 2.1.0
  • Datasets 2.14.5
  • Tokenizers 0.15.1
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