readme: ---
  language:
  - nl
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - thomashaas/ggz
  metrics:
  - wer
  model-index:
  - name: Parla NL
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: GGZ
        type: thomashaas/ggz
        config: nl
        split: test
        args: nl
      metrics:
      - name: Wer
        type: wer
        value: 9.82347932216382
  ---
  
  <!-- 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. -->
  
  # Parla NL
  
  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the GGZ dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2049
  - Wer: 9.8234
  
  ## 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
  - 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     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.055         | 2.01  | 1000 | 0.2009          | 11.2481 |
  | 0.0134        | 4.02  | 2000 | 0.2549          | 10.1520 |
  | 0.0035        | 6.03  | 3000 | 0.2219          | 10.6326 |
  | 0.0021        | 8.04  | 4000 | 0.2259          | 10.3550 |
  | 0.0009        | 10.05 | 5000 | 0.2049          | 9.8234 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.1.dev0
  - Tokenizers 0.13.2
  