readme: ---
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - google/fleurs
  metrics:
  - wer
  model-index:
  - name: Whisper Large 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: 54.06850588964662
  ---
  
  <!-- 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 Large Pashto
  
  This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the google/fleurs ps_af dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8623
  - Wer: 54.0685
  
  ## 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: 8
  - eval_batch_size: 4
  - seed: 42
  - gradient_accumulation_steps: 8
  - 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: 50
  - training_steps: 700
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch  | Step | Validation Loss | Wer     |
  |:-------------:|:------:|:----:|:---------------:|:-------:|
  | 1.2281        | 16.59  | 100  | 1.0951          | 69.3118 |
  | 0.7529        | 33.3   | 200  | 0.8693          | 57.5635 |
  | 0.5372        | 49.89  | 300  | 0.8399          | 54.7350 |
  | 0.4398        | 66.59  | 400  | 0.8623          | 54.0685 |
  | 0.3244        | 83.3   | 500  | 0.9098          | 54.7505 |
  | 0.238         | 99.89  | 600  | 0.9607          | 55.3782 |
  | 0.2014        | 116.59 | 700  | 1.0077          | 55.9206 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  