readme: ---
  language:
  - kn
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: Whisper Small Kn - Bharat Ramanathan
    results:
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: google/fleurs
        type: google/fleurs
        config: kn_in
        split: test
      metrics:
      - type: wer
        value: 25.54
        name: WER
  ---
  
  <!-- 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 Kn - Bharat Ramanathan
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1398
  - Wer: 23.8167
  
  ## 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: 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      |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.4126        | 0.1   | 500  | 2.2797          | 127.2639 |
  | 0.2099        | 0.1   | 1000 | 0.1774          | 28.2494  |
  | 0.1736        | 0.2   | 1500 | 0.1565          | 27.5733  |
  | 0.1506        | 0.3   | 2000 | 0.1514          | 26.0331  |
  | 0.1373        | 0.4   | 2500 | 0.1494          | 24.4177  |
  | 0.1298        | 0.5   | 3000 | 0.1456          | 25.0563  |
  | 0.1198        | 1.06  | 3500 | 0.1436          | 24.4177  |
  | 0.1102        | 0.1   | 4000 | 0.1452          | 24.2675  |
  | 0.1097        | 0.2   | 4500 | 0.1402          | 24.3050  |
  | 0.105         | 0.3   | 5000 | 0.1398          | 23.8167  |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  