readme: ---
  license: apache-2.0
  language:
  - pa
  tags:
  - generated_from_trainer
  - whisper-event
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Small Punjabi
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 pa-IN
        type: mozilla-foundation/common_voice_11_0
        config: pa-IN
        split: test
        args: pa-IN
      metrics:
      - name: Wer
        type: wer
        value: 39.04688700999232
  ---
  
  <!-- 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 Punjabi
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the common_voice_11_0 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5991
  - Wer: 39.0469
  
  ## 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
  - training_steps: 400
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.4346        | 5.01  | 50   | 0.3902          | 49.6797 |
  | 0.0728        | 11.0  | 100  | 0.3811          | 40.7379 |
  | 0.009         | 16.02 | 150  | 0.4924          | 39.5081 |
  | 0.0028        | 22.0  | 200  | 0.5309          | 38.7394 |
  | 0.0008        | 27.02 | 250  | 0.5687          | 38.6369 |
  | 0.0006        | 33.01 | 300  | 0.5859          | 39.0213 |
  | 0.0005        | 38.02 | 350  | 0.5954          | 39.0981 |
  | 0.0005        | 44.01 | 400  | 0.5991          | 39.0469 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  