readme: ---
  license: apache-2.0
  tags:
    - whisper-event
    - generated_from_trainer
    - hf-asr-leaderboard
  datasets:
    - arbml/mgb2
  metrics:
    - wer
  model-index:
    - name: Whisper Medium ar - Zaid Alyafeai
      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: 34.28
        - 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: 12.04
  ---
  
  
  <!-- 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-medium
  
  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8488
  - Wer: 16.5882
  
  ## 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: 32
  - eval_batch_size: 16
  - 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     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.2963        | 0.1   | 1000  | 0.9115          | 27.3641 |
  | 0.2676        | 0.2   | 2000  | 0.8796          | 24.1024 |
  | 0.3166        | 0.3   | 3000  | 0.8467          | 20.1700 |
  | 0.2797        | 0.4   | 4000  | 0.8756          | 29.4889 |
  | 0.2302        | 0.5   | 5000  | 0.8523          | 19.6414 |
  | 0.2803        | 0.6   | 6000  | 0.8715          | 19.7413 |
  | 0.2794        | 0.7   | 7000  | 0.8548          | 18.6840 |
  | 0.2173        | 0.8   | 8000  | 0.8543          | 17.9019 |
  | 0.217         | 0.9   | 9000  | 0.8518          | 16.3840 |
  | 0.1718        | 1.0   | 10000 | 0.8488          | 16.5882 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  