readme: ---
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  - hf-asr-leaderboard
  - pashto
  - ps
  datasets:
  - google/fleurs
  metrics:
  - wer
  model-index:
  - name: Whisper Medium Pashto
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: google/fleurs
        type: google/fleurs
        args: 'config: ps_af, split: test'
      metrics:
      - name: Wer
        type: wer
        value: 49.4855
  ---
  
  <!-- 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 Medium Pashto
  
  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the google/fleurs ps_af dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.4807
  - Wer: 50.5448
  
  ## 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: 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: 10
  - training_steps: 1200
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch  | Step | Validation Loss | Wer     |
  |:-------------:|:------:|:----:|:---------------:|:-------:|
  | 0.0334        | 14.29  | 100  | 1.0348          | 50.0908 |
  | 0.0021        | 28.57  | 200  | 1.1971          | 49.4855 |
  | 0.0007        | 42.86  | 300  | 1.2651          | 49.7352 |
  | 0.0006        | 57.14  | 400  | 1.3084          | 49.9697 |
  | 0.0005        | 71.43  | 500  | 1.3479          | 50.0605 |
  | 0.0004        | 85.71  | 600  | 1.3835          | 50.3027 |
  | 0.0004        | 100.0  | 700  | 1.4139          | 50.4540 |
  | 0.0004        | 114.29 | 800  | 1.4382          | 50.4616 |
  | 0.0004        | 128.57 | 900  | 1.4545          | 50.5297 |
  | 0.0003        | 142.86 | 1000 | 1.4603          | 50.5675 |
  | 0.0003        | 157.14 | 1100 | 1.4750          | 50.5599 |
  | 0.0003        | 171.43 | 1200 | 1.4807          | 50.5448 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  