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[EMNLP2023] Generative Adversarial Training with Perturbed Token Detection for Model Robustness

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GenerativeAT

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).

Prepare Environment

  1. Create environment and install requirement packages using provided environment.yml:
conda env create -f environment.yml
conda activate GenerAT
  1. Download pre-trained model
    • Download pytorch_model.bin and pytorch_model.generator.bin from huggingface and put it in ./deberta-v3-large .
  2. Download glue data
python download_glue_data.py

Train

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

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[EMNLP2023] Generative Adversarial Training with Perturbed Token Detection for Model Robustness

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