README.md

metadata

language:
  - ja
license: other
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - Elite35P-Server/EliteVoiceProject
metrics:
  - wer
model-index:
  - name: Whisper Base Japanese Elite
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Elite35P-Server/EliteVoiceProject twitter
          type: Elite35P-Server/EliteVoiceProject
          config: twitter
          split: test
          args: twitter
        metrics:
          - name: Wer
            type: wer
            value: 11.585365853658537

Whisper Base Japanese Elite

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

• Loss: 0.1459
• Wer: 11.5854

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: 8
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: constant_with_warmup
• lr_scheduler_warmup_steps: 50
• training_steps: 1000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0009	29.01	1000	0.1459	11.5854

Framework versions

• Transformers 4.26.0.dev0
• Pytorch 1.13.0+cu117
• Datasets 2.8.1.dev0
• Tokenizers 0.13.2