readme: ---
  widget:
  - src: https://huggingface.co/datasets/kalisia/TongaASR_Space_Examples/blob/main/220929-200958_toi_97d_elicit_17.wav
    example_title: Tonga Speech Sample 1
  - example_title: toi sample 1
    src: https://huggingface.co/datasets/kalisia/TongaASR_Space_Examples/blob/main/220929-200958_toi_97d_elicit_17.wav
  
  model-index:
  - name: whisper-tiny
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Tonga
        type: tongaspeech_asr
        config: clean
        split: test
        args: 
          language: toi
      metrics:
      - name: Test WER
        type: wer
        value: 52.59
  license: apache-2.0
  tags:
  - automatic-speech-recognition
  ---
  
  <!-- 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-tonga_5hrs
  
  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: 0.9145
  - Wer: 52.2928
  
  ## 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: 2
  - eval_batch_size: 2
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 8
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 1000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer      |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 3.3353        | 1.45  | 200  | 1.9984          | 113.0627 |
  | 1.7712        | 2.9   | 400  | 1.2576          | 72.0656  |
  | 1.1476        | 4.35  | 600  | 1.0129          | 59.8233  |
  | 1.004         | 5.79  | 800  | 0.9406          | 53.2183  |
  | 0.9169        | 7.25  | 1000 | 0.9145          | 52.2928  |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  