readme: ---
  language:
  - nl
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Large v2 Dutch
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 nl
        type: mozilla-foundation/common_voice_11_0
        config: nl
        split: test
        args: nl
      metrics:
      - name: Wer
        type: wer
        value: 5.895082837397793
  ---
  
  <!-- 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 v2 Dutch
  
  This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the mozilla-foundation/common_voice_11_0 nl dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1310
  - Wer: 5.8951
  
  ## 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
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 500
  - training_steps: 12000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.138         | 0.08  | 1000  | 0.2101          | 11.5288 |
  | 0.121         | 0.17  | 2000  | 0.1987          | 10.4458 |
  | 0.1413        | 0.25  | 3000  | 0.1956          | 10.4672 |
  | 0.1158        | 0.33  | 4000  | 0.1778          | 9.3729  |
  | 0.1056        | 0.42  | 5000  | 0.1795          | 9.7792  |
  | 0.056         | 1.05  | 6000  | 0.1560          | 7.6927  |
  | 0.0323        | 1.14  | 7000  | 0.1460          | 7.1445  |
  | 0.0213        | 1.22  | 8000  | 0.1491          | 7.2844  |
  | 0.051         | 1.3   | 9000  | 0.1457          | 6.9587  |
  | 0.0196        | 1.39  | 10000 | 0.1420          | 6.6086  |
  | 0.019         | 2.02  | 11000 | 0.1303          | 6.0553  |
  | 0.0124        | 2.11  | 12000 | 0.1310          | 5.8951  |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu117
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2
  