readme: ---
  language:
  - id
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  - magic_data
  - titml
  - google/fleurs
  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
      metrics:
      - name: Wer
        type: wer
        value: 18.28368532693904
  ---
  
  # 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, magic_data, titml and google/fleurs dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2409
  - Wer: 18.2837
  
  ## 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: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 10000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.4103        | 0.66  | 1000  | 0.3802          | 27.0497 |
  | 0.2682        | 1.32  | 2000  | 0.3223          | 22.9365 |
  | 0.2381        | 1.99  | 3000  | 0.2884          | 20.8245 |
  | 0.1606        | 2.65  | 4000  | 0.2727          | 20.1928 |
  | 0.1246        | 3.31  | 5000  | 0.2596          | 18.9984 |
  | 0.1344        | 3.97  | 6000  | 0.2482          | 18.7540 |
  | 0.0975        | 4.63  | 7000  | 0.2471          | 18.6388 |
  | 0.0916        | 5.29  | 8000  | 0.2436          | 18.9615 |
  | 0.0854        | 5.96  | 9000  | 0.2413          | 18.3114 |
  | 0.0812        | 6.62  | 10000 | 0.2409          | 18.2837 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  