readme: ---
  license: apache-2.0
  tags:
    - whisper-event
    - generated_from_trainer
    - hf-asr-leaderboard
  datasets:
    - arbml/mgb2
  metrics:
    - wer
  model-index:
    - name: Whisper Small ar - Mohammad AlMarzouq
      results:
        - task:
            name: Automatic Speech Recognition
            type: automatic-speech-recognition
          dataset:
            name: mozilla-foundation/common_voice_11_0
            type: mozilla-foundation/common_voice_11_0
            config: ar
            split: test
            args: ar
          metrics:
            - name: Wer
              type: wer
              value: 43.14
        - task:
            name: Automatic Speech Recognition
            type: automatic-speech-recognition
          dataset:
            name: google/fleurs
            type: google/fleurs
            config: ar_eg
            split: test
            args: ar
          metrics:
            - name: Wer
              type: wer
              value: 16.69
  ---
  
  <!-- 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. -->
  
  # openai/whisper-small
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9750
  - Wer: 21.3693
  
  ## 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: 64
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 10000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.3559        | 0.1   | 1000  | 0.9147          | 29.3252 |
  | 0.3154        | 0.2   | 2000  | 1.1353          | 26.5718 |
  | 0.359         | 0.3   | 3000  | 0.9208          | 25.3987 |
  | 0.273         | 0.4   | 4000  | 0.9591          | 24.3877 |
  | 0.2326        | 0.5   | 5000  | 0.9207          | 21.9052 |
  | 0.2992        | 1.04  | 6000  | 0.9445          | 22.4556 |
  | 0.2265        | 1.14  | 7000  | 0.9660          | 21.2230 |
  | 0.2059        | 1.24  | 8000  | 0.9785          | 20.9551 |
  | 0.2239        | 1.34  | 9000  | 0.9637          | 21.6300 |
  | 0.2163        | 1.44  | 10000 | 0.9750          | 21.3693 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  