readme: ---
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - data/copas
  metrics:
  - wer
  model-index:
  - name: Whisper Small dysarthric Dutch
    results:
    - task:
        name: Automatic Speech Recognition
        type: automatic-speech-recognition
      dataset:
        name: data/copas copas-full
        type: data/copas
        config: copas-full
        split: test
        args: copas-full
      metrics:
      - name: Wer
        type: wer
        value: 25.08155128669808
  ---
  
  <!-- 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 dysarthric Dutch
  
  This model is a fine-tuned version of [qmeeus/whisper-small-nl](https://huggingface.co/qmeeus/whisper-small-nl) on the data/copas copas-full dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3314
  - Wer: 25.0816
  
  ## 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: 32
  - eval_batch_size: 32
  - seed: 42
  - gradient_accumulation_steps: 2
  - total_train_batch_size: 64
  - 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     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.3462        | 0.1   | 500  | 0.3721          | 29.9746 |
  | 0.1205        | 1.1   | 1000 | 0.3286          | 26.4226 |
  | 0.0642        | 2.1   | 1500 | 0.3139          | 25.2628 |
  | 0.0443        | 3.1   | 2000 | 0.3169          | 25.0453 |
  | 0.0356        | 4.1   | 2500 | 0.3226          | 25.0634 |
  | 0.0321        | 5.09  | 3000 | 0.3237          | 24.7191 |
  | 0.0317        | 6.09  | 3500 | 0.3322          | 24.7735 |
  | 0.0347        | 7.09  | 4000 | 0.3355          | 25.0634 |
  | 0.0357        | 8.09  | 4500 | 0.3364          | 25.2265 |
  | 0.0318        | 9.09  | 5000 | 0.3314          | 25.0816 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.12.1+cu116
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  