readme: ---
  language:
  - pa
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Small Panjabi
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 11.0
        type: mozilla-foundation/common_voice_11_0
        config: pa-IN
        split: test
        args: pa-IN
      metrics:
      - name: Wer
        type: wer
        value: 36.10043556238791
  ---
  
  <!-- 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 Panjabi
  
  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: 0.6084
  - Wer: 36.1004
  
  ## 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: 16
  - eval_batch_size: 64
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 50
  - training_steps: 1000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.349         | 5.86  | 100  | 0.4664          | 49.1929 |
  | 0.0175        | 11.74 | 200  | 0.4633          | 39.1494 |
  | 0.0052        | 17.63 | 300  | 0.5317          | 37.7146 |
  | 0.0014        | 23.51 | 400  | 0.5521          | 36.4079 |
  | 0.0009        | 29.4  | 500  | 0.5731          | 35.4599 |
  | 0.0002        | 35.29 | 600  | 0.5806          | 35.6649 |
  | 0.0001        | 41.17 | 700  | 0.5933          | 35.7161 |
  | 0.0001        | 47.06 | 800  | 0.6016          | 35.9211 |
  | 0.0001        | 52.91 | 900  | 0.6067          | 36.0492 |
  | 0.0001        | 58.8  | 1000 | 0.6084          | 36.1004 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  