readme: ---
  language:
  - fy
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - mozilla-foundation/common_voice_11_0
  metrics:
  - wer
  model-index:
  - name: Whisper Small Frisian
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: mozilla-foundation/common_voice_11_0 fy-NL
        type: mozilla-foundation/common_voice_11_0
        config: fy-NL
        split: test
        args: fy-NL
      metrics:
      - name: Wer
        type: wer
        value: 21.03
  ---
  
  <!-- 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 fy-NL - RuudVelo
  
  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 test set:
  - Loss: 0.1443
  - Wer: 21.03
  
  ## 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: 64
  - eval_batch_size: 8
  - training_steps: 5000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss |  Step | Validation Loss | Wer    |
  |:-------------:|:-----:|:---------------:|:------:|
  | 0.0053        |  1000 | 0.4201          | 21.64  |
  | 0.0008        |  2000 | 0.4607          | 21.03  |
  | 0.0004        |  3000 | 0.4853          | 21.11  |
  | 0.0003        |  4000 | 0.5015          | 21.14  |
  | 0.0002        |  5000 | 0.5084          | 21.20  |
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1.dev0
  - Tokenizers 0.13.2