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metadata
language:
  - ja
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Base Japanese
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0 ja
          type: mozilla-foundation/common_voice_11_0
          config: ja
          split: test
          args: ja
        metrics:
          - name: Wer
            type: wer
            value: 21.991788980318223

Whisper Base Japanese

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

  • Loss: 0.6532
  • Wer: 21.9918

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: 32
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 500
  • training_steps: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.3273 3.02 1000 0.4225 20.8253
0.0923 7.0 2000 0.4643 21.2200
0.0164 10.02 3000 0.5403 22.9627
0.006 14.01 4000 0.5820 21.0861
0.0046 17.02 5000 0.5852 22.0728
0.0034 21.01 6000 0.6113 21.6623
0.0028 24.03 7000 0.6582 22.3266
0.0025 28.01 8000 0.6350 22.2332
0.0029 32.0 9000 0.6468 22.1098
0.0014 35.02 10000 0.6532 21.9918

Framework versions

  • Transformers 4.26.0.dev0
  • Pytorch 1.13.1+cu117
  • Datasets 2.8.1.dev0
  • Tokenizers 0.13.2