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whisper-large-v3-turbo-zh-TW-clean-1

This model is a fine-tuned version of openai/whisper-large-v3-turbo on the JacobLinCool/common_voice_16_1_zh_TW_clean_preprocessed dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2641
  • Wer: 40.0723
  • Cer: 11.4336

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: 0.0005
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 32
  • 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: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Cer Validation Loss Wer
No log 0 0 22.9952 2.8297 83.7420
2.0577 0.9987 377 14.2907 0.2666 47.9904
1.9482 2.0 755 14.4991 0.2770 47.9703
1.1107 2.9987 1132 15.0615 0.2886 48.4124
0.7225 4.0 1510 13.4020 0.2736 46.2420
0.5901 4.9987 1887 13.7309 0.2759 45.2572
0.4879 6.0 2265 12.9777 0.2740 44.9759
0.1874 6.9987 2642 12.7316 0.2663 44.2524
0.0544 8.0 3020 12.2295 0.2712 42.6648
0.0128 8.9987 3397 11.6068 0.2669 40.8963
0.004 9.9868 3770 11.4336 0.2641 40.0723
0.004 9.9868 3770 0.2641 40.0723 11.4336

Framework versions

  • PEFT 0.13.2
  • Transformers 4.46.0
  • Pytorch 2.4.0
  • Datasets 3.0.2
  • Tokenizers 0.20.1
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Evaluation results

  • Wer on JacobLinCool/common_voice_16_1_zh_TW_clean_preprocessed
    self-reported
    40.072