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 Medium 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: 3.8273540533062804
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: google/fleurs id_id
        type: google/fleurs 
        config: id_id
        split: test
      metrics:
      - name: Wer
        type: wer
        value: 9.74
    
  ---
  
  # Whisper Medium Indonesian
  
  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the 
  Indonesian mozilla-foundation/common_voice_11_0, magic_data, titml and google/fleurs dataset. It achieves the following 
  results:
  ### CV11 test split:
  - Loss: 0.0698
  - Wer: 3.8274
  ### Google/fleurs test split:
  - Wer: 9.74
  
  ## Usage
  
  ```python
  from transformers import pipeline
  transcriber = pipeline(
    "automatic-speech-recognition", 
    model="cahya/whisper-medium-id"
  )
  transcriber.model.config.forced_decoder_ids = (
    transcriber.tokenizer.get_decoder_prompt_ids(
      language="id" 
      task="transcribe"
    )
  )
  transcription = transcriber("my_audio_file.mp3")
  ```
  
  ## 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: 16
  - 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 0.0427        | 0.33  | 1000  | 0.0664          | 4.3807 |
  | 0.042         | 0.66  | 2000  | 0.0658          | 3.9426 |
  | 0.0265        | 0.99  | 3000  | 0.0657          | 3.8274 |
  | 0.0211        | 1.32  | 4000  | 0.0679          | 3.8366 |
  | 0.0212        | 1.66  | 5000  | 0.0682          | 3.8412 |
  | 0.0206        | 1.99  | 6000  | 0.0683          | 3.8689 |
  | 0.0166        | 2.32  | 7000  | 0.0711          | 3.9657 |
  | 0.0095        | 2.65  | 8000  | 0.0717          | 3.9980 |
  | 0.0122        | 2.98  | 9000  | 0.0714          | 3.9795 |
  | 0.0049        | 3.31  | 10000 | 0.0720          | 3.9887 |
  
  ## Evaluation
  
  We evaluated the model using the test split of two datasets, the [Common Voice 11](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0) 
  and the [Google Fleurs](https://huggingface.co/datasets/google/fleurs). 
  As Whisper can transcribe casing and punctuation, we also evaluate its performance using raw and normalized text.
  (lowercase + removal of punctuations). The results are as follows:
  
  ### Common Voice 11
  
  |                                                                           | WER  |
  |---------------------------------------------------------------------------|------|
  | [cahya/whisper-medium-id](https://huggingface.co/cahya/whisper-medium-id) | 3.83 |
  | [openai/whisper-medium](https://huggingface.co/openai/whisper-medium)     | 12.62  |
  
  ### Google/Fleurs
  
  |                                                                                                             | WER  |
  |-------------------------------------------------------------------------------------------------------------|------|
  | [cahya/whisper-medium-id](https://huggingface.co/cahya/whisper-medium-id)                      | 9.74 |
  | [cahya/whisper-medium-id](https://huggingface.co/cahya/whisper-medium-id) + text normalization | tbc  |
  | [openai/whisper-medium](https://huggingface.co/openai/whisper-medium)                                       | 10.2 |
  | [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) + text normalization                  | tbc  |
  | 
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  