readme: ---
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  - automatic-speech-recognition
  - hf-asr-leaderboard
  - pashto
  - ps
  datasets:
  - google/fleurs
  metrics:
  - wer
  model-index:
  - name: Whisper Small Pashto
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: google/fleurs ps_af
        type: google/fleurs
        args: 'config: ps_af, split: test'
      metrics:
      - name: Wer
        type: wer
        value: 56.651029055690074
  ---
  
  <!-- 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
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the google/fleurs ps_af dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.2273
  - Wer: 56.6510
  
  ## 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: 3e-07
  - train_batch_size: 64
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 800
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch  | Step | Validation Loss | Wer     |
  |:-------------:|:------:|:----:|:---------------:|:-------:|
  | 2.1183        | 3.7    | 100  | 1.3170          | 76.9522 |
  | 0.8565        | 7.41   | 200  | 0.9367          | 61.9930 |
  | 0.2246        | 11.11  | 300  | 0.9642          | 58.8302 |
  | 0.054         | 14.81  | 400  | 1.0876          | 57.9903 |
  | 0.0159        | 18.52  | 500  | 1.1798          | 57.8768 |
  | 0.0045        | 22.22  | 600  | 1.2309          | 56.6510 |
  | 0.0026        | 100.0  | 700  | 1.2581          | 56.8478 |
  | 0.0023        | 114.29 | 800  | 1.2710          | 56.7570 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  