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: 59.64817110973342
  ---
  
  <!-- 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: 0.7901
  - Wer: 59.6482
  - Cer: 27.0947
  
  ## 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: 600
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     | Cer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
  | 1.1215        | 2.38  | 100  | 0.9444          | 68.3354 | 30.2694 |
  | 0.8268        | 4.75  | 200  | 0.8267          | 63.2440 | 28.2636 |
  | 0.6912        | 7.14  | 300  | 0.7959          | 62.2443 | 28.2123 |
  | 0.5725        | 9.52  | 400  | 0.7896          | 60.5859 | 27.6920 |
  | 0.5231        | 11.89 | 500  | 0.7884          | 59.8574 | 27.1273 |
  | 0.4752        | 14.28 | 600  | 0.7901          | 59.6482 | 27.0947 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  