readme: ---
  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 Large V2 Japanese
    results:
    - task:
        type: automatic-speech-recognition
        name: 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:
      - type: wer
        value: 8.1166
        name: Wer
      - type: cer
        value: 5.0032
        name: Cer
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # openai/whisper-large-v2
  
  This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the mozilla-foundation/common_voice_11_0 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2352
  - Wer: 8.1166
  - Cer: 5.0032
  
  ## 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: 8
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 10000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     | Cer    |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|
  | 0.0897        | 0.1   | 1000  | 0.1884          | 11.0068 | 6.6992 |
  | 0.0396        | 0.2   | 2000  | 0.1749          | 9.7399  | 5.9350 |
  | 0.036         | 1.1   | 3000  | 0.1698          | 9.1419  | 5.6781 |
  | 0.012         | 1.2   | 4000  | 0.1849          | 9.3041  | 5.7661 |
  | 0.0151        | 2.09  | 5000  | 0.1879          | 9.1959  | 5.6761 |
  | 0.0047        | 2.19  | 6000  | 0.2097          | 8.6706  | 5.4422 |
  | 0.0046        | 3.09  | 7000  | 0.2040          | 8.8277  | 5.4717 |
  | 0.0015        | 3.19  | 8000  | 0.2260          | 8.4949  | 5.3101 |
  | 0.0013        | 4.09  | 9000  | 0.2339          | 8.3716  | 5.1471 |
  | 0.0005        | 4.19  | 10000 | 0.2352          | 8.1166  | 5.0032 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  