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: 22.163827473722364
  ---
  
  <!-- 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: 0.4702
  - Wer: 22.1638
  
  ## 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: 0.0001
  - 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: 10000
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Wer     |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|
  | 0.1618        | 0.05  | 500   | 0.3787          | 28.9235 |
  | 0.0583        | 1.05  | 1000  | 0.3732          | 25.7702 |
  | 0.0382        | 2.05  | 1500  | 0.4001          | 25.4621 |
  | 0.0316        | 3.05  | 2000  | 0.4081          | 24.7010 |
  | 0.0169        | 4.05  | 2500  | 0.4325          | 24.1935 |
  | 0.0153        | 5.05  | 3000  | 0.4325          | 33.4179 |
  | 0.0074        | 6.05  | 3500  | 0.4367          | 23.9398 |
  | 0.0096        | 7.05  | 4000  | 0.4390          | 23.3055 |
  | 0.0054        | 8.05  | 4500  | 0.4441          | 23.7042 |
  | 0.0032        | 9.04  | 5000  | 0.4493          | 23.2693 |
  | 0.004         | 10.04 | 5500  | 0.4524          | 23.3418 |
  | 0.0048        | 11.04 | 6000  | 0.4498          | 23.7224 |
  | 0.001         | 12.04 | 6500  | 0.4577          | 22.8887 |
  | 0.0002        | 13.04 | 7000  | 0.4577          | 22.0913 |
  | 0.0001        | 14.04 | 7500  | 0.4616          | 22.1276 |
  | 0.0001        | 15.04 | 8000  | 0.4639          | 22.2726 |
  | 0.0001        | 16.04 | 8500  | 0.4662          | 22.1095 |
  | 0.0001        | 17.04 | 9000  | 0.4684          | 22.1457 |
  | 0.0001        | 18.04 | 9500  | 0.4697          | 22.1457 |
  | 0.0001        | 19.04 | 10000 | 0.4702          | 22.1638 |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.12.1+cu116
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  