readme: ---
  language:
  - da
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Medium Danish (Common Voice Corpus 11.0)
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 da
        type: mozilla-foundation/common_voice_11_0
        config: da
        split: test
        args: da
      metrics:
      - name: Wer
        type: wer
        value: 16.13361388742767
  ---
  
  <!-- 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 Danish (Common Voice Corpus 11.0)
  
  This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_11_0 da dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5081
  - Wer: 16.1336
  
  ## 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     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.0229        | 7.01  | 1000  | 0.4464          | 16.5124 |
  | 0.0072        | 15.0  | 2000  | 0.5081          | 16.1336 |
  | 0.0048        | 22.01 | 3000  | 0.5193          | 16.6597 |
  | 0.0034        | 30.0  | 4000  | 0.5715          | 16.8964 |
  | 0.0005        | 37.01 | 5000  | 0.5998          | 16.4440 |
  | 0.0007        | 45.01 | 6000  | 0.5908          | 16.8017 |
  | 0.0001        | 53.0  | 7000  | 0.6093          | 16.2336 |
  | 0.0001        | 60.01 | 8000  | 0.6405          | 16.3335 |
  | 0.0           | 68.0  | 9000  | 0.6524          | 16.2493 |
  | 0.0           | 75.01 | 10000 | 0.6569          | 16.2283 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  