readme: ---
  license: mit
  tags:
  - generated_from_keras_callback
  model-index:
  - name: DLL888/roberta-base-squad
    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. -->
  
  # DLL888/roberta-base-squad
  
  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 0.7054
  - Train End Logits Accuracy: 0.8022
  - Train Start Logits Accuracy: 0.7586
  - Validation Loss: 0.8224
  - Validation End Logits Accuracy: 0.7692
  - Validation Start Logits Accuracy: 0.7402
  - 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': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 10570, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 500, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
  - training_precision: mixed_float16
  
  ### Training results
  
  | Train Loss | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch |
  |:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
  | 1.1613     | 0.7038                    | 0.6632                      | 0.8676          | 0.7626                         | 0.7342                           | 0     |
  | 0.7054     | 0.8022                    | 0.7586                      | 0.8224          | 0.7692                         | 0.7402                           | 1     |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - TensorFlow 2.9.2
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  