readme: ---
  language:
  - ps
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - google/fleurs
  metrics:
  - wer
  model-index:
  - name: Whisper Small Pashto - Augmented
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: google/fleurs
        type: google/fleurs
        args: 'config: ps_af, split: test'
      metrics:
      - name: Wer
        type: wer
        value: 53.62439467312349
  ---
  
  <!-- 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 Pashto - Augmented
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the google/fleurs dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.6979
  - Wer: 53.6244
  - Cer: 22.6847
  
  ## 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: 16
  - 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: 30
  - training_steps: 300
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer      | Cer      |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
  | 0.9683        | 1.19  | 100  | 0.8812          | 139.3765 | 131.6166 |
  | 0.6848        | 2.38  | 200  | 0.7543          | 145.9973 | 151.3369 |
  | 0.5548        | 3.57  | 300  | 0.6979          | 53.6244  | 22.6847  |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu117
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  