# 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](https://arxiv.org/pdf/1406.2661.pdf). 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](https://rajpurkar.github.io/SQuAD-explorer/) dataset.

Electra-base-vn is trained on more 148gb text with max length 512.

You can download tensorflow version at [Electra base TF version](https://drive.google.com/drive/folders/1hN0LiOlMfNDDQVo2bgEYHd03I-xXDLVr?usp=sharing)
### Contact information
For personal communication related to this project, please contact Nha Nguyen Van (nha282@gmail.com).