Adversarial Text Generation by Search and Learning
Our 7 datasets are:
Required packages are listed in the requirements.txt file:
pip install -r requirements.txt
- Run the following code to generate the adversaries:
python command_dataset_model.py
Here we explain each required argument in details:
- --data_set: The path to the dataset. We used the public datasets datasets.
- --victim: Name of the target model such as ''bert''. trained model parameters.
- --bm_model: Our generated finely tuned BM_Model,we shared the trained model parameters.
- --train_classification: Used to generate victim models.
- --model: All core model codes of ATGSL.
In case someone may want to use our generated adversary results towards the benchmark data directly, here it is.