readme: ---
  language:
  - ps
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - google/fleurs
  metrics:
  - wer
  model-index:
  - name: Whisper Base Pashto - Augmented
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: google/fleurs
        type: google/fleurs
        config: ps_af
        split: test
        args: ps_af
      metrics:
      - name: Wer
        type: wer
        value: 57.611985472154956
  ---
  
  <!-- 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 Base Pashto - Augmented
  
  This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the google/fleurs dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8723
  - Wer: 57.6120
  - Cer: 26.6468
  
  ## 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: 8
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 30
  - training_steps: 1000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     | Cer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
  | 0.9708        | 2.38  | 100  | 0.8821          | 64.0133 | 27.3253 |
  | 0.7477        | 4.75  | 200  | 0.8062          | 59.9576 | 26.4079 |
  | 0.6229        | 7.14  | 300  | 0.7855          | 58.3081 | 26.3193 |
  | 0.4833        | 9.52  | 400  | 0.7870          | 57.5288 | 24.8855 |
  | 0.4084        | 11.89 | 500  | 0.7980          | 56.5224 | 25.2214 |
  | 0.3323        | 14.28 | 600  | 0.8201          | 56.6662 | 25.3317 |
  | 0.283         | 16.66 | 700  | 0.8406          | 57.7406 | 26.8674 |
  | 0.2598        | 19.05 | 800  | 0.8538          | 57.2866 | 26.0386 |
  | 0.2235        | 21.42 | 900  | 0.8697          | 58.2703 | 26.6819 |
  | 0.2202        | 23.8  | 1000 | 0.8723          | 57.6120 | 26.6468 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  