readme: ---
  language:
  - nn
  license: apache-2.0
  tags:
  - hf-asr-leaderboard
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: whisper-small-npsc
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: Common Voice 11.0
        type: mozilla-foundation/common_voice_11_0
        config: 16K_mp3_bokmaal
        split: train
        args: 16K_mp3_bokmaal
      metrics:
      - name: Wer
        type: wer
        value: 12.925418803583286
  ---
  
  <!-- 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-npsc
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2028
  - Wer: 12.9254
  
  ## 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: 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: 6000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Wer     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.3922        | 0.18  | 500  | 0.3975          | 24.2055 |
  | 0.2893        | 0.36  | 1000 | 0.3139          | 20.1507 |
  | 0.2471        | 0.54  | 1500 | 0.2733          | 17.4449 |
  | 0.2159        | 0.72  | 2000 | 0.2488          | 16.2681 |
  | 0.2195        | 0.89  | 2500 | 0.2304          | 15.0577 |
  | 0.1178        | 1.07  | 3000 | 0.2245          | 14.5968 |
  | 0.1099        | 1.25  | 3500 | 0.2183          | 14.1118 |
  | 0.1059        | 1.43  | 4000 | 0.2136          | 13.7914 |
  | 0.1156        | 1.61  | 4500 | 0.2072          | 13.7491 |
  | 0.1025        | 1.79  | 5000 | 0.2034          | 13.1515 |
  | 0.1123        | 1.97  | 5500 | 0.2006          | 13.0284 |
  | 0.0734        | 2.15  | 6000 | 0.2028          | 12.9254 |
  
  
  ### Framework versions
  
  - Transformers 4.25.0.dev0
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  