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Whisper Small Japanese

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

  • Loss: 0.4232
  • Wer: 13.4679
  • Cer: 8.6022

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 Cer
0.0167 7.0 1000 0.3066 13.6740 8.5733
0.0021 14.01 2000 0.3579 13.8733 8.7816
0.0006 21.01 3000 0.4025 13.5794 8.6173
0.0004 28.01 4000 0.4232 13.4679 8.6022
0.0004 35.01 5000 0.4319 13.4747 8.6213

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.12.1+cu113
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2
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Dataset used to train vumichien/whisper-small-ja

Evaluation results