readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: openai/whisper-medium
    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. -->
  
  # 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: 0.2790
  - Wer: 8.3986
  - Cer: 5.2582
  
  ## 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     | Cer    |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|
  | 0.1691        | 1.01  | 1000  | 0.1871          | 10.1740 | 6.3509 |
  | 0.0916        | 2.02  | 2000  | 0.1691          | 8.9797  | 5.5499 |
  | 0.0452        | 3.03  | 3000  | 0.1902          | 8.9814  | 5.5867 |
  | 0.0213        | 4.04  | 4000  | 0.2062          | 8.9375  | 5.6531 |
  | 0.0096        | 5.05  | 5000  | 0.2284          | 8.7331  | 5.6202 |
  | 0.0041        | 6.05  | 6000  | 0.2395          | 8.5051  | 5.3009 |
  | 0.0022        | 7.06  | 7000  | 0.2535          | 8.5507  | 5.3640 |
  | 0.001         | 8.07  | 8000  | 0.2656          | 8.5557  | 5.3791 |
  | 0.0006        | 9.08  | 9000  | 0.2721          | 8.4037  | 5.2739 |
  | 0.0004        | 10.09 | 10000 | 0.2790          | 8.3986  | 5.2582 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  