readme: ---
  language:
  - en
  license: apache-2.0
  tags:
  - en-asr-leaderboard
  - generated_from_trainer
  datasets:
  - mn367/radio-test-dataset
  model-index:
  - name: Whisper Medium 1hr
    results: []
  ---
  
  <!-- 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 1hr
  
  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Radio dataset dataset.
  It achieves the following results on the evaluation set:
  - eval_loss: 0.6053
  - eval_wer: 17.5426
  - eval_runtime: 651.6941
  - eval_samples_per_second: 2.363
  - eval_steps_per_second: 0.296
  - epoch: 37.5
  - step: 900
  
  ## 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-06
  - train_batch_size: 16
  - 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: 1600
  - mixed_precision_training: Native AMP
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  