metadata

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.

Question Answering with Hugging Face Transformers and Keras 🤗❤️

This model is a fine-tuned version of 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 question answering dataset. ⁉️

Training procedure

Find the notebook in Keras Examples here. ❤️

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