readme: ---
  language:
  - id
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  model-index:
  - name: Whisper Medium ID - FLEURS-CV
    results:
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: google/fleurs
        type: google/fleurs
        config: id_id
        split: test
      metrics:
      - type: wer
        value: 7.8
        name: WER
      - type: cer
        value: 2.43
        name: CER
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0
        type: mozilla-foundation/common_voice_11_0
        config: id
        split: test
      metrics:
      - type: wer
        value: 8.67
        name: WER
      - type: cer
        value: 2.71
        name: CER
  ---
  
  <!-- 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 Medium ID - FLEURS-CV
  
  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:
  - eval_loss: 0.2563
  - eval_wer: 8.4690
  - eval_runtime: 2961.9108
  - eval_samples_per_second: 1.453
  - eval_steps_per_second: 0.091
  - epoch: 14.29
  - step: 5000
  
  ## 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
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  