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 Small Danish - Robust
    results:
    - task:
        type: automatic-speech-recognition
        name: 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:
      - type: wer
        value: 32.3250920568122
        name: Wer
      - type: wer
        value: 28.09
        name: WER
  ---
  
  <!-- 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 Small Danish - Robust
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 da dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7926
  - Wer: 32.3251
  
  ## 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: 5e-05
  - train_batch_size: 64
  - eval_batch_size: 32
  - 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: 5000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.0232        | 15.15 | 1000 | 0.7538          | 35.5813 |
  | 0.0061        | 30.3  | 2000 | 0.7933          | 34.3766 |
  | 0.0016        | 45.45 | 3000 | 0.7993          | 33.5823 |
  | 0.0003        | 60.61 | 4000 | 0.7986          | 31.6097 |
  | 0.0002        | 75.76 | 5000 | 0.7901          | 32.1357 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.1+cu117
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  