readme: ---
  license: apache-2.0
  tags:
  - whisper-event
  - generated_from_trainer
  datasets:
  - data/copas
  metrics:
  - wer
  model-index:
  - name: Whisper Small 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: 0.0
  ---
  
  <!-- 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 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: 0.0015
  - Wer: 0.0
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | 0.1291        | 2.03  | 500  | 0.2953          | 25.0681 |
  | 0.0524        | 5.03  | 1000 | 0.1626          | 13.9118 |
  | 0.0403        | 8.03  | 1500 | 0.0825          | 6.5450  |
  | 0.0349        | 11.03 | 2000 | 0.0409          | 2.5652  |
  | 0.0122        | 14.03 | 2500 | 0.0173          | 0.6619  |
  | 0.0053        | 17.03 | 3000 | 0.0068          | 0.0822  |
  | 0.0032        | 20.02 | 3500 | 0.0037          | 0.0173  |
  | 0.0022        | 23.02 | 4000 | 0.0024          | 0.0     |
  | 0.0018        | 26.02 | 4500 | 0.0018          | 0.0     |
  | 0.0016        | 29.02 | 5000 | 0.0015          | 0.0     |
  
  
  ### Framework versions
  
  - Transformers 4.26.0.dev0
  - Pytorch 1.12.1+cu116
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  