readme: ---
  tags:
  - generated_from_keras_callback
  model-index:
  - name: Svenskmodell
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information Keras had access to. You should
  probably proofread and complete it, then remove this comment. -->
  
  # Svenskmodell
  
  This model is a fine-tuned version of [KB/bert-base-swedish-cased](https://huggingface.co/KB/bert-base-swedish-cased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 0.3411
  - Train End Logits Accuracy: 0.8882
  - Train Start Logits Accuracy: 0.8838
  - Validation Loss: 1.4988
  - Validation End Logits Accuracy: 0.6713
  - Validation Start Logits Accuracy: 0.6669
  - Epoch: 3
  
  ## 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:
  - optimizer: {'name': 'Adam', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 28792, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
  - training_precision: float32
  
  ### Training results
  
  | Train Loss | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch |
  |:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
  | 1.2392     | 0.6241                    | 0.6197                      | 1.0970          | 0.6588                         | 0.6543                           | 0     |
  | 0.7549     | 0.7615                    | 0.7569                      | 1.1185          | 0.6673                         | 0.6665                           | 1     |
  | 0.5005     | 0.8376                    | 0.8323                      | 1.3299          | 0.6571                         | 0.6503                           | 2     |
  | 0.3411     | 0.8882                    | 0.8838                      | 1.4988          | 0.6713                         | 0.6669                           | 3     |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - TensorFlow 2.6.4
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  