readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: bert-hoofdthemas
    results: []
  ---
  
  <!-- 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. -->
  
  # bert-hoofdthemas
  
  This model is a fine-tuned version of [GroNLP/bert-base-dutch-cased](https://huggingface.co/GroNLP/bert-base-dutch-cased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.1925
  - Accuracy: 0.7327
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 6
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 1.0712        | 1.0   | 2107  | 0.9968          | 0.7035   |
  | 0.8567        | 2.0   | 4214  | 0.9297          | 0.7230   |
  | 0.6865        | 3.0   | 6321  | 0.9586          | 0.7346   |
  | 0.5546        | 4.0   | 8428  | 0.9767          | 0.7387   |
  | 0.4429        | 5.0   | 10535 | 1.0708          | 0.7370   |
  | 0.3395        | 6.0   | 12642 | 1.1925          | 0.7327   |
  
  
  ### Framework versions
  
  - Transformers 4.21.3
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  