Our paper is accepted in SpLU workshop of ACL2021.
paper:
https://aclanthology.org/2021.splurobonlp-1.5/
Flease follow https://github.com/airsplay/R2R-EnvDrop to set up the environment.
bash run/agent.bash 0
0 is the id of GPU. It will train the agent and save the snapshot under snap/agent/. Unseen success rate would be around 46%.
bash run/bt_envdrop.bash 0
0 is the id of GPU. It will load the pre-trained agent and run back translation with environmental dropout.
Modify the parameters in param.py to the corresponding path, and the following link is the corresponding features. https://drive.google.com/file/d/1Mf2yiP4mdTUwSn6r9aNiCjcsqLsoYRHM/view?usp=sharing