readme: ---
  language:
  - id
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Tiny Indonesian
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 id
        type: mozilla-foundation/common_voice_11_0
        config: id
        split: test
        args: id
      metrics:
      - name: Wer
        type: wer
        value: 32.421838974453564
  ---
  
  <!-- 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 Tiny Indonesian
  
  This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the mozilla-foundation/common_voice_11_0 id dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6202
  - Wer: 32.4218
  
  ## 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: 2e-05
  - train_batch_size: 64
  - eval_batch_size: 32
  - 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 | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.3823        | 4.95  | 500  | 0.5251          | 33.4732 |
  | 0.0495        | 9.9   | 1000 | 0.5700          | 33.3902 |
  | 0.0077        | 14.85 | 1500 | 0.6202          | 32.4218 |
  | 0.0031        | 19.8  | 2000 | 0.6616          | 32.5371 |
  | 0.0019        | 24.75 | 2500 | 0.6873          | 32.7954 |
  | 0.0014        | 29.7  | 3000 | 0.7056          | 33.5700 |
  | 0.0011        | 34.65 | 3500 | 0.7204          | 33.7960 |
  | 0.0009        | 39.6  | 4000 | 0.7327          | 33.7729 |
  | 0.0008        | 44.55 | 4500 | 0.7400          | 33.9113 |
  | 0.0007        | 49.5  | 5000 | 0.7428          | 33.3441 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  