readme: ---
  language:
  - ko
  license: apache-2.0
  tags:
  - hf-asr-leaderboard
  - generated_from_trainer
  - whisper-event
  datasets:
  - kresnik/zeroth_korean
  metrics:
  - wer
  model-index:
  - name: Whisper Small Korean
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Zeroth Korean
        type: kresnik/zeroth_korean
        config: clean
        split: test
        args: 'split: test'
      metrics:
      - name: Wer
        type: wer
        value: 6.761029965366662
  ---
  
  <!-- 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 Korean
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Zeroth Korean dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0899
  - Wer: 6.7610
  
  ## 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: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 4000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.1277        | 0.72  | 1000 | 0.1489          | 12.2271 |
  | 0.0379        | 1.44  | 2000 | 0.1053          | 6.7159  |
  | 0.0138        | 2.16  | 3000 | 0.0918          | 6.0382  |
  | 0.0141        | 2.87  | 4000 | 0.0899          | 6.7610  |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0a0+d0d6b1f
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  