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Whisper Small TW on Chinese base

This model is a fine-tuned version of Jingmiao/whisper-small-chinese_base on the mozilla-foundation/common_voice_11_0 zh-TW dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2601
  • Wer: 41.9038

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: 64
  • 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: 500
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0071 6.02 1000 0.2364 42.6407
0.0008 13.02 2000 0.2601 41.9038
0.0004 20.01 3000 0.2771 42.3951
0.0003 27.0 4000 0.2867 42.6407
0.0002 33.02 5000 0.2901 42.6407

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.1+cu117
  • Datasets 2.8.1.dev0
  • Tokenizers 0.13.2
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Dataset used to train Jingmiao/whisper-small-chineseBaseTW

Evaluation results