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: 60.05599273607748
  ---
  
  <!-- 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: 0.8714
  - Wer: 60.0560
  
  ## 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-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: 100
  - training_steps: 1300
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.9153        | 2.5   | 100  | 1.0240          | 68.9864 |
  | 0.6865        | 5.0   | 200  | 0.8968          | 61.7660 |
  | 0.5474        | 7.5   | 300  | 0.8744          | 60.5554 |
  | 0.4646        | 10.0  | 400  | 0.8710          | 60.0560 |
  | 0.4557        | 12.5  | 500  | 0.8732          | 59.4658 |
  | 0.3882        | 15.0  | 600  | 0.8819          | 59.0648 |
  | 0.3346        | 17.5  | 700  | 0.9032          | 59.4809 |
  | 0.2947        | 20.0  | 800  | 0.9144          | 59.7685 |
  | 0.2724        | 22.5  | 900  | 0.9289          | 58.9815 |
  | 0.2785        | 25.0  | 1000 | 0.9339          | 59.2010 |
  | 0.2454        | 27.5  | 1100 | 0.9439          | 59.1934 |
  | 0.2297        | 30.0  | 1200 | 0.9485          | 59.0421 |
  | 0.2383        | 33.33 | 1300 | 0.9529          | 59.0799 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu117
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  