readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: nandysoham/6-clustered
    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/6-clustered
  
  This model is a fine-tuned version of [Rocketknight1/distilbert-base-uncased-finetuned-squad](https://huggingface.co/Rocketknight1/distilbert-base-uncased-finetuned-squad) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 0.5973
  - Train End Logits Accuracy: 0.8147
  - Train Start Logits Accuracy: 0.8012
  - Validation Loss: 0.7844
  - Validation End Logits Accuracy: 0.7760
  - Validation Start Logits Accuracy: 0.7754
  - Epoch: 1
  
  ## 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': 850, '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 |
  |:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
  | 0.8725     | 0.7440                    | 0.7329                      | 0.7849          | 0.7673                         | 0.7713                           | 0     |
  | 0.5973     | 0.8147                    | 0.8012                      | 0.7844          | 0.7760                         | 0.7754                           | 1     |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - TensorFlow 2.9.2
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  