readme: ---
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - google/fleurs
  metrics:
  - wer
  model-index:
  - name: Whisper Tiny Pashto
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: google/fleurs ps_af
        type: google/fleurs
        config: ps_af
        split: test
        args: ps_af
      metrics:
      - name: Wer
        type: wer
        value: 69.61259079903148
  ---
  
  <!-- 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 Tiny Pashto
  
  This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the google/fleurs ps_af dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.0742
  - Wer: 69.6126
  
  ## 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: 32
  - eval_batch_size: 16
  - seed: 42
  - gradient_accumulation_steps: 2
  - 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: 500
  - training_steps: 500
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer      |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 1.8225        | 14.29 | 100  | 1.7608          | 105.3193 |
  | 0.7281        | 28.57 | 200  | 1.0742          | 69.6126  |
  | 0.2329        | 42.86 | 300  | 1.1192          | 67.0248  |
  | 0.0247        | 57.14 | 400  | 1.3495          | 66.3741  |
  | 0.0057        | 71.43 | 500  | 1.5055          | 67.2896  |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  