readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - wer
  model-index:
  - name: whisper-medium-bem
    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-bem
  
  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: 0.3519
  - Wer: 33.5877
  
  ## 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: 4
  - eval_batch_size: 4
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 8
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 5000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.6509        | 0.34  | 500  | 0.4872          | 50.9031 |
  | 0.5212        | 0.67  | 1000 | 0.3972          | 40.5156 |
  | 0.3957        | 1.01  | 1500 | 0.3451          | 36.4793 |
  | 0.2956        | 1.34  | 2000 | 0.3421          | 37.3866 |
  | 0.2987        | 1.68  | 2500 | 0.3206          | 34.5374 |
  | 0.1665        | 2.02  | 3000 | 0.3290          | 34.1135 |
  | 0.1557        | 2.35  | 3500 | 0.3334          | 35.0462 |
  | 0.1345        | 2.69  | 4000 | 0.3374          | 33.8506 |
  | 0.0617        | 3.02  | 4500 | 0.3445          | 33.6216 |
  | 0.0661        | 3.36  | 5000 | 0.3519          | 33.5877 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  