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_large_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: 26.367876079171644
  ---
  
  <!-- 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 persian
  
  This model is a fine-tuned version of [anuragshas/whisper-large-v2-hi](https://huggingface.co/anuragshas/whisper-large-v2-hi) on the mozilla-foundation/common_voice_11_0 fa dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3047
  - Wer: 26.3679
  
  ## 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-05
  - train_batch_size: 8
  - eval_batch_size: 16
  - seed: 42
  - distributed_type: multi-GPU
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 16
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 100
  - training_steps: 1000
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.2948        | 0.19  | 250  | 0.4258          | 35.6023 |
  | 0.2443        | 0.39  | 500  | 0.3650          | 30.9747 |
  | 0.1956        | 0.58  | 750  | 0.3228          | 28.0196 |
  | 0.1715        | 0.78  | 1000 | 0.3047          | 26.3679 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1+cu117
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  