readme: ---
  language:
  - km
  license: apache-2.0
  tags:
  - hf-asr-leaderboard
  - generated_from_trainer
  datasets:
  - openslr
  metrics:
  - wer
  model-index:
  - name: Whisper Small Km - Kak Soky
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: SLR42
        type: openslr
        args: 'config: km, split: test'
      metrics:
      - name: Wer
        type: wer
        value: 35.665399239543724
  ---
  
  <!-- 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 Km - Kak Soky
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the SLR42 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1471
  - Wer: 35.6654
  
  ## Model description
  
  The model was fine-tuned on both encoder-decoder of transformer-based.
  
  ## Intended uses & limitations
  
  The training data is limited, thus the performance is also limited to only reading speech and a limited domain (tourism).
  
  ## Training and evaluation data
  
  The training and evaluation data was split in a 9:1 ratio from Google Text-to-speech corpus.
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 1e-05
  - train_batch_size: 2
  - eval_batch_size: 4
  - 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     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.3639        | 0.76  | 1000 | 0.3452          | 71.9392 |
  | 0.1553        | 1.53  | 2000 | 0.2025          | 49.0494 |
  | 0.0565        | 2.29  | 3000 | 0.1664          | 39.9240 |
  | 0.0334        | 3.06  | 4000 | 0.1471          | 35.6654 |
  
  
  ### Framework versions
  
  - Transformers 4.25.0.dev0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.0
  - Tokenizers 0.13.2
  