readme: ---
  license: apache-2.0
  tags:
    - whisper-event
    - generated_from_trainer
    - hf-asr-leaderboard
  datasets:
    - arbml/mgb2
  metrics:
    - wer
  model-index:
    - name: Whisper Large V2 - 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: 38.23
        - 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: 11.60
  ---
  
  
  <!-- 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-large-v2
  
  This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8091
  - Wer: 17.7875
  
  ## 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
  - distributed_type: multi-GPU
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 10000
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.2528        | 0.2   | 2000  | 0.9370          | 22.1311 |
  | 0.2718        | 0.4   | 4000  | 0.8721          | 24.9294 |
  | 0.2745        | 0.6   | 6000  | 0.8770          | 20.5292 |
  | 0.2157        | 0.8   | 8000  | 0.8774          | 18.1018 |
  | 0.1729        | 1.0   | 10000 | 0.8091          | 17.7875 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  