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Whisper Small Taiwanese

This model is a fine-tuned version of openai/whisper-small on the Common Voice 15.0 and 16.1 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3916
  • Wer: 68.5703

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
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.4172 0.32 1000 0.4641 82.9494
0.2962 0.64 2000 0.3834 73.8040
0.229 0.97 3000 0.3537 70.0423
0.1994 1.29 4000 0.3685 71.1599
0.1693 1.61 5000 0.3551 67.8206
0.1398 1.93 6000 0.3526 67.6707
0.1032 2.25 7000 0.3836 69.4834
0.0745 2.58 8000 0.3839 68.5566
0.0558 2.9 9000 0.3916 68.5703

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.1.2
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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