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whisper-small-zh-tw

Automatic Speech Recognition
Transformers
PyTorch
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Chinese
whisper
whisper-event
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metadata
language:
  - zh
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Small Traditional Chinese
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0 zh-TW
          type: mozilla-foundation/common_voice_11_0
          config: zh-TW
          split: test
          args: zh-TW
        metrics:
          - name: Wer
            type: wer
            value: 32.594792142530835

Whisper Small Traditional Chinese

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

  • Loss: 0.3250
  • Wer: 32.5948

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: 800
  • training_steps: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.3465 1.05 200 0.3499 41.9324
0.2137 2.1 400 0.2953 36.2951
0.1255 4.01 600 0.2927 33.7232
0.0509 5.06 800 0.3149 34.0566
0.0164 6.11 1000 0.3250 32.5948

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.0+cu116
  • Datasets 2.7.1.dev0
  • Tokenizers 0.13.2