readme: ---
  language:
  - ja
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  model-index:
  - name: Whisper Small JA - Lorenzo Concina
    results: []
  ---
  
  <!-- 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 Small JA - Lorenzo Concina
  
  This model is a fine-tuned version of [SVJ Japanese dataset](https://huggingface.co/SVJ Japanese dataset) on the Common Voice 11.0 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5596
  - Cer: 17.7261
  
  ## 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: 4
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 5000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Cer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.0682        | 0.33  | 1000 | 0.6098          | 19.9133 |
  | 0.0229        | 0.67  | 2000 | 0.5501          | 18.1911 |
  | 0.0457        | 1.0   | 3000 | 0.5745          | 19.3174 |
  | 0.0123        | 1.34  | 4000 | 0.5315          | 18.2546 |
  | 0.0238        | 1.67  | 5000 | 0.5596          | 17.7261 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0
  - Datasets 2.7.1
  - Tokenizers 0.11.0
  