readme: ---
  language:
  - 'no'
  - nb
  - multilingual
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - NbAiLab/NCC_S
  metrics:
  - wer
  model-index:
  - name: Whisper Large Norwegian
    results:
    - task:
        type: automatic-speech-recognition
        name: Automatic Speech Recognition
      dataset:
        name: NbAiLab/NCC_S
        type: NbAiLab/NCC_S
        config: 'no'
        split: validation
        args: 'no'
      metrics:
      - type: wer
        value: 12.058465286236297
        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 Large Norwegian
  
  This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the NbAiLab/NCC_S dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2784
  - Wer: 12.0585
  
  ## 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-06
  - train_batch_size: 12
  - eval_batch_size: 6
  - 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     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.6755        | 0.2   | 1000 | 0.3108          | 14.3118 |
  | 0.673         | 0.4   | 2000 | 0.3004          | 13.4592 |
  | 0.6378        | 0.6   | 3000 | 0.2865          | 13.0024 |
  | 0.5776        | 0.8   | 4000 | 0.2809          | 12.6675 |
  | 0.5962        | 1.0   | 5000 | 0.2784          | 12.0585 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.11.0
  