Whisper Small zh-TW - hanson92828

This model is a fine-tuned version of openai/whisper-small on the Common Voice 16.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2087
  • Wer: 203.2213

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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 4000

Training results

Training Loss Epoch Step Validation Loss Wer
0.0974 1.3263 1000 0.1997 167.3042
0.0218 2.6525 2000 0.1987 228.9309
0.0094 3.9788 3000 0.2022 221.2603
0.0025 5.3050 4000 0.2087 203.2213

Framework versions

  • Transformers 4.46.0.dev0
  • Pytorch 2.4.0+cu121
  • Datasets 2.19.2
  • Tokenizers 0.20.1
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Dataset used to train hanson92828/whisper-small-chinese-2

Evaluation results