readme: ---
  language:
  - kn
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: Whisper Tiny 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: 43.7
        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 Tiny 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: 0.3057
  - Wer: 46.3937
  
  ## 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: 150
  - eval_batch_size: 64
  - 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: 3000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer      |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 1.4091        | 0.1   | 300  | 1.4915          | 101.5026 |
  | 1.1294        | 0.2   | 600  | 1.2845          | 94.7408  |
  | 0.5426        | 0.3   | 900  | 0.4621          | 64.2374  |
  | 0.4128        | 1.02  | 1200 | 0.3695          | 54.6582  |
  | 0.3629        | 1.12  | 1500 | 0.3414          | 52.9677  |
  | 0.3321        | 1.22  | 1800 | 0.3249          | 50.3005  |
  | 0.3066        | 1.32  | 2100 | 0.3181          | 48.9106  |
  | 0.2958        | 2.03  | 2400 | 0.3136          | 47.7836  |
  | 0.2883        | 2.13  | 2700 | 0.3055          | 46.6191  |
  | 0.2857        | 2.23  | 3000 | 0.3057          | 46.3937  |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  