noflm
update model card README.md
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metadata
language:
  - ja
license: other
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - Elite35P-Server/EliteVoiceProject
metrics:
  - wer
model-index:
  - name: Whisper Small Japanese Elite
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Elite35P-Server/EliteVoiceProject twitch
          type: Elite35P-Server/EliteVoiceProject
          config: twitch
          split: test
          args: twitch
        metrics:
          - name: Wer
            type: wer
            value: 23.296888141295206

Whisper Small Japanese Elite

This model is a fine-tuned version of openai/whisper-small on the Elite35P-Server/EliteVoiceProject twitch dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9180
  • Wer: 23.2969

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 100
  • training_steps: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0033 18.0 1000 0.6728 25.3154
0.008 37.0 2000 0.6984 23.3810
0.0002 56.0 3000 0.7486 24.4743
0.0001 75.0 4000 0.7753 24.4743
0.0 94.0 5000 0.8014 24.0538
0.0 113.0 6000 0.8244 24.3902
0.0 132.0 7000 0.8468 23.8015
0.0 150.0 8000 0.8699 23.4651
0.0 169.0 9000 0.8936 23.2128
0.0 188.0 10000 0.9180 23.2969

Framework versions

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