readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: distilbertbaseuncasedz
    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. -->
  
  # distilbertbaseuncasedz
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 0.5368
  - Train End Logits Accuracy: 0.8401
  - Train Start Logits Accuracy: 0.8078
  - Validation Loss: 1.2427
  - Validation End Logits Accuracy: 0.7050
  - Validation Start Logits Accuracy: 0.6725
  - 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': 29508, '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 |
  |:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
  | 1.3338     | 0.6448                    | 0.6045                      | 1.1322          | 0.6906                         | 0.6563                           | 0     |
  | 0.9044     | 0.7466                    | 0.7090                      | 1.0996          | 0.7032                         | 0.6720                           | 1     |
  | 0.6756     | 0.8042                    | 0.7680                      | 1.1416          | 0.7047                         | 0.6718                           | 2     |
  | 0.5368     | 0.8401                    | 0.8078                      | 1.2427          | 0.7050                         | 0.6725                           | 3     |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - TensorFlow 2.6.4
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  