readme: ---
  language:
  - id
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  - magic_data
  - TITML
  metrics:
  - wer
  model-index:
  - name: Whisper Large 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: 6.248270773771097
  ---
  
  <!-- 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 Large Indonesian
  
  This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the mozilla-foundation/common_voice_11_0, magic_data, titml id dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2034
  - Wer: 6.2483
  
  ## 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-06
  - train_batch_size: 12
  - eval_batch_size: 12
  - 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 0.1516        | 0.5   | 1000  | 0.1730          | 6.5664 |
  | 0.1081        | 1.0   | 2000  | 0.1638          | 6.3682 |
  | 0.0715        | 1.49  | 3000  | 0.1803          | 6.2713 |
  | 0.1009        | 1.99  | 4000  | 0.1796          | 6.2667 |
  | 0.0387        | 2.49  | 5000  | 0.2054          | 6.4927 |
  | 0.0494        | 2.99  | 6000  | 0.2034          | 6.2483 |
  | 0.0259        | 3.48  | 7000  | 0.2226          | 6.3497 |
  | 0.0265        | 3.98  | 8000  | 0.2274          | 6.4004 |
  | 0.0232        | 4.48  | 9000  | 0.2443          | 6.5618 |
  | 0.015         | 4.98  | 10000 | 0.2413          | 6.4927 |
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  