readme: ---
  language:
  - fa
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper small Persian
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 fa
        type: mozilla-foundation/common_voice_11_0
        config: fa
        split: test
      metrics:
      - name: Wer
        type: wer
        value: 32.8995086472
  ---
  
  <!-- 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 Persian
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 fa dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4924
  - Wer: 32.8995
  
  ## 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-06
  - train_batch_size: 8
  - eval_batch_size: 16
  - seed: 42
  - distributed_type: multi-GPU
  - num_devices: 4
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 64
  - total_eval_batch_size: 64
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 5000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.5533        | 1.56  | 500  | 0.7044          | 54.5499 |
  | 0.3951        | 3.12  | 1000 | 0.5893          | 47.5210 |
  | 0.3296        | 4.67  | 1500 | 0.5429          | 42.6451 |
  | 0.2662        | 6.23  | 2000 | 0.5223          | 40.6644 |
  | 0.2535        | 7.79  | 2500 | 0.5045          | 38.5304 |
  | 0.224         | 9.35  | 3000 | 0.5002          | 36.8822 |
  | 0.2204        | 10.9  | 3500 | 0.4967          | 35.3076 |
  | 0.2024        | 12.46 | 4000 | 0.4951          | 34.9883 |
  | 0.2099        | 14.02 | 4500 | 0.4921          | 34.9842 |
  | 0.1836        | 15.58 | 5000 | 0.4924          | 34.8995 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  