README.md

ELECTRA

Introduction

ELECTRA is a method for self-supervised language representation learning. It can be used to pre-train transformer networks using relatively little compute. ELECTRA models are trained to distinguish "real" input tokens vs "fake" input tokens generated by another neural network, similar to the discriminator of a GAN. At small scale, ELECTRA achieves strong results even when trained on a single GPU. At large scale, ELECTRA achieves state-of-the-art results on the SQuAD 2.0 dataset.

Contact information

For personal communication related to this project, please contact Nha Nguyen Van (nha282@gmail.com). You can download tensorflow version at Electra base TF version