This is the source code for the paper Generative Adversarial Training with Perturbed Token Detection for Robustness . This project is build on DeBERTa-V3 and has tested on Ubuntu 20.04.5 LTS with single GPU (V100 32GB).

1. Create environment and install requirement packages using provided environment.yml:

conda env create -f environment.yml
conda activate GenerAT

2. Download pre-trained model
   • Download pytorch_model.bin and pytorch_model.generator.bin from huggingface and put it in ./deberta-v3-large .
3. Download glue data

python download_glue_data.py

Run the following bash scripts, it will train the model on corresponding dataset and report evaluation metrics.

• adv-rte

bash ./adv_glue/rte.sh

• adv-sst-2

bash ./adv_glue/sst2.sh

• adv-mnli

bash ./adv_glue/mnli.sh

• adv-qnli

bash ./adv_glue/qnli.sh

• adv-qqp

bash ./adv_glue/qqp.sh