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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 large-v2 nan-tw only char
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0 nan-tw
          type: mozilla-foundation/common_voice_11_0
          config: nan-tw
          split: test
          args: nan-tw
        metrics:
          - name: Wer
            type: wer
            value: 45.37404580152672

Whisper large-v2 nan-tw only char

This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/common_voice_11_0 nan-tw dataset. It achieves the following results on the evaluation set:

  • Loss: 1.0351
  • Wer: 45.3740
  • Cer: 45.4573

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: 2
  • eval_batch_size: 2
  • 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
0.6011 1.04 1000 1.1100 55.0229 55.2068
0.1773 2.08 2000 1.2055 58.6565 58.7685
0.015 3.13 3000 1.0932 48.6412 48.8077
0.0131 5.01 4000 1.0531 45.7099 45.8497
0.0001 6.05 5000 1.0351 45.3740 45.4573

Framework versions

  • Transformers 4.27.0.dev0
  • Pytorch 1.13.1+cu117
  • Datasets 2.8.0
  • Tokenizers 0.13.2