readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: nandysoham/Dell-theme-finetuned-overfinetuned
    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. -->
  
  # nandysoham/Dell-theme-finetuned-overfinetuned
  
  This model is a fine-tuned version of [nandysoham/distilbert-base-uncased-finetuned-squad](https://huggingface.co/nandysoham/distilbert-base-uncased-finetuned-squad) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 0.4305
  - Train End Logits Accuracy: 0.7857
  - Train Start Logits Accuracy: 0.8006
  - Validation Loss: 2.3316
  - Validation End Logits Accuracy: 0.1647
  - Validation Start Logits Accuracy: 0.2118
  - Epoch: 9
  
  ## 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': 210, '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 |
  |:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
  | 1.5691     | 0.5179                    | 0.5119                      | 1.2093          | 0.4588                         | 0.4588                           | 0     |
  | 0.9333     | 0.6101                    | 0.5833                      | 1.2828          | 0.3176                         | 0.3647                           | 1     |
  | 0.7924     | 0.6042                    | 0.5982                      | 1.4627          | 0.2824                         | 0.2824                           | 2     |
  | 0.6858     | 0.6905                    | 0.6786                      | 1.5630          | 0.3059                         | 0.2941                           | 3     |
  | 0.6562     | 0.6518                    | 0.6815                      | 1.7647          | 0.2235                         | 0.2118                           | 4     |
  | 0.5996     | 0.7054                    | 0.6994                      | 2.0109          | 0.2118                         | 0.2471                           | 5     |
  | 0.5277     | 0.7440                    | 0.7589                      | 2.1286          | 0.1765                         | 0.2000                           | 6     |
  | 0.4810     | 0.7679                    | 0.7798                      | 2.2263          | 0.1529                         | 0.2000                           | 7     |
  | 0.4488     | 0.8036                    | 0.7887                      | 2.2999          | 0.1529                         | 0.1882                           | 8     |
  | 0.4305     | 0.7857                    | 0.8006                      | 2.3316          | 0.1647                         | 0.2118                           | 9     |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - TensorFlow 2.9.2
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  