Transformers Qa

🚀 Question Answering with Hugging Face Transformers and Keras 🤗❤️

This model is designed to address question - answering tasks. It leverages the power of Hugging Face Transformers and Keras, offering an efficient solution for retrieving answers from given contexts.

🚀 Quick Start

This model is a fine - tuned version of [distilbert - base - cased](https://huggingface.co/distilbert - base - cased) on the SQuAD dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.9300
• Validation Loss: 1.1437
• Epoch: 1

✨ Features

• Fine - tuned Model: Based on distilbert - base - cased, fine - tuned for question - answering tasks.
• Trained with Popular Frameworks: Utilizes 🤗Transformers and ❤️Keras for training.

📚 Documentation

Model description

Question answering model based on distilbert - base - cased, trained with 🤗Transformers + ❤️Keras.

Intended uses & limitations

This model is trained for the 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

Framework versions

• Transformers 4.16.0.dev0
• TensorFlow 2.6.0
• Datasets 1.16.2.dev0
• Tokenizers 0.10.3

📄 License

This model is released under the Apache 2.0 license.