readme: ---
  license: mit
  tags:
  - generated_from_keras_callback
  model-index:
  - name: DLL888/deberta-v3-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/deberta-v3-base-squad
  
  This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the [SQuAD](https://huggingface.co/datasets/squad) dataset.
  
  It achieves the following results on the evaluation set:
  
  - Exact Match: 88.08893093661305
  - F1: 93.75543944888847
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  More information needed
  
  ## Training procedure
  
  ### Training Machine
  
  Trained in Google Colab Pro with the following specs:
  
  - A100-SXM4-40GB
  - NVIDIA-SMI 460.32.03
  - Driver Version: 460.32.03
  - CUDA Version: 11.2
  
  Training took about 26 minutes for two epochs.
  
  ### 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': 10538, '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: float32
  
  ### Training results
  
  | Train Loss | Train End Logits Accuracy | Train Start Logits Accuracy | Validation Loss | Validation End Logits Accuracy | Validation Start Logits Accuracy | Epoch |
  |:----------:|:-------------------------:|:---------------------------:|:---------------:|:------------------------------:|:--------------------------------:|:-----:|
  | 1.0540     | 0.7261                    | 0.6885                      | 0.7617          | 0.7841                         | 0.7530                           | 0     |
  | 0.6248     | 0.8212                    | 0.7777                      | 0.7594          | 0.7873                         | 0.7569                           | 1     |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - TensorFlow 2.9.2
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  