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 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
  ---
  
  <!-- 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. -->
  
  # Whisper Base Japanese
  
  This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/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
  