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 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: 63.10532687651331
  ---
  
  <!-- 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: 1.1800
  - Wer: 63.1053
  
  ## 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: 5200
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch  | Step | Validation Loss | Wer      |
  |:-------------:|:------:|:----:|:---------------:|:--------:|
  | 2.0871        | 14.29  | 100  | 2.0102          | 230.2739 |
  | 1.465         | 28.57  | 200  | 1.4969          | 137.2427 |
  | 1.1617        | 42.86  | 300  | 1.2716          | 76.3242  |
  | 1.0019        | 57.14  | 400  | 1.1645          | 71.3756  |
  | 0.9052        | 71.43  | 500  | 1.1051          | 69.7866  |
  | 0.8334        | 85.71  | 600  | 1.0691          | 68.2657  |
  | 0.7838        | 100.0  | 700  | 1.0483          | 67.1686  |
  | 0.7539        | 114.29 | 800  | 1.0363          | 66.4195  |
  | 0.7377        | 128.57 | 900  | 1.0297          | 66.2001  |
  | 0.7325        | 142.86 | 1000 | 1.0277          | 66.0033  |
  | 0.6952        | 157.14 | 1100 | 1.0122          | 65.0575  |
  | 0.6531        | 171.43 | 1200 | 1.0014          | 64.4219  |
  | 0.6189        | 185.71 | 1300 | 0.9945          | 63.7939  |
  | 0.5993        | 200.0  | 1400 | 0.9896          | 63.3550  |
  | 0.5757        | 214.29 | 1500 | 0.9864          | 63.2264  |
  | 0.5601        | 228.57 | 1600 | 0.9845          | 62.9162  |
  | 0.5482        | 242.86 | 1700 | 0.9833          | 62.8178  |
  | 0.5382        | 257.14 | 1800 | 0.9827          | 62.8405  |
  | 0.5325        | 271.43 | 1900 | 0.9823          | 62.7648  |
  | 0.5287        | 285.71 | 2000 | 0.9822          | 62.8178  |
  | 0.3494        | 357.14 | 2500 | 1.0026          | 61.6147  |
  | 0.2287        | 428.57 | 3000 | 1.0533          | 61.5163  |
  | 0.1525        | 500.0  | 3500 | 1.1041          | 62.0536  |
  | 0.1089        | 571.43 | 4000 | 1.1451          | 62.5076  |
  | 0.0871        | 642.86 | 4500 | 1.1704          | 62.9313  |
  | 0.0797        | 714.29 | 5000 | 1.1791          | 63.1659  |
  | 0.0799        | 728.57 | 5100 | 1.1800          | 63.1053  |
  | 0.0791        | 742.86 | 5200 | 1.1803          | 63.1129  |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  