readme: ---
  datasets:
  - squad
  license: apache-2.0
  tags: 
  - generated_from_keras_callback
  metrics: 
  - f1
  model-index: 
  - name: transformers-qa
    results: 
    - task: 
        name: "Question Answering"
        type: question-answering
      dataset: 
        type: squad
        name: SQuAD
        args: en
      metrics:
        []
  widget: 
    - context: "Keras is an API designed for human beings, not machines. Keras follows best practices for reducing cognitive load: it offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear and actionable feedback upon user error."
  ---
  <!-- 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. -->
  
  # Question Answering with Hugging Face Transformers and Keras 🤗❤️
  
  This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on SQuAD dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 0.9300
  - Validation Loss: 1.1437
  - Epoch: 1
  
  ## Model description
  
  Question answering model based on distilbert-base-cased, trained with 🤗Transformers + ❤️Keras.
  
  ## Intended uses & limitations
  
  This model is trained for Question Answering tutorial for Keras.io.
  
  ## Training and evaluation data
  
  It is trained on [SQuAD](https://huggingface.co/datasets/squad) question answering dataset. ⁉️ 
  
  ## Training procedure
  
  Find the notebook in Keras Examples [here](https://keras.io/examples/nlp/question_answering/). ❤️
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - optimizer: {'name': 'Adam', 'learning_rate': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
  - training_precision: mixed_float16
  
  ### Training results
  
  | Train Loss | Validation Loss | Epoch |
  |:----------:|:---------------:|:-----:|
  | 1.5145     | 1.1500          | 0     |
  | 0.9300     | 1.1437          | 1     |
   
  
  ### Framework versions
  
  - Transformers 4.16.0.dev0
  - TensorFlow 2.6.0
  - Datasets 1.16.2.dev0
  - Tokenizers 0.10.3
  