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Whisper medium nan-tw

This model is a fine-tuned version of openai/whisper-medium on the mozilla-foundation/common_voice_11_0 nan-tw dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9100
  • Wer: 42.0709
  • Cer: 22.3681

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: 8
  • 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: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
0.0568 5.0 1000 0.7769 48.2706 26.0890
0.0057 10.0 2000 0.8438 44.0722 23.9270
0.0041 15.01 3000 0.8740 42.8540 22.9554
0.0001 20.01 4000 0.9041 42.1797 22.5496
0.0001 25.01 5000 0.9100 42.0709 22.3681

Framework versions

  • Transformers 4.27.0.dev0
  • Pytorch 1.13.1+cu117
  • Datasets 2.8.0
  • Tokenizers 0.13.2
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Dataset used to train thomas0104/whisper_medium_nan_tw

Evaluation results

  • Cer-char on mozilla-foundation/common_voice_11_0 nan-tw
    self-reported
    45.038
  • Cer-rome on mozilla-foundation/common_voice_11_0 nan-tw
    self-reported
    31.566