The code for the SelfExplain framework (https://arxiv.org/abs/2103.12279)
Currently, this repo supports SelfExplain-XLNet version for SST-2 dataset. The other datasets and models shown in the paper will be updated soon.
Data for preprocessing available in data/ folder
On a python shell, do the following for installing the parser
>>> import benepar
>>> benepar.download('benepar_en3')sh scripts/run_preprocessing.shsh scripts/run_self_explain.sh(In Progress)
python model/infer_model.py
--ckpt $PATH_TO_BEST_DEV_CHECKPOINT \
--concept_map $DATA_FOLDER/concept_idx.json \
--batch_size $BS \
--paths_output_loc $PATH_TO_OUTPUT_PREDS \
--dev_file $PATH_TO_DEV_FILEComing Soon ...
@misc{rajagopal2021selfexplain,
title={SelfExplain: A Self-Explaining Architecture for Neural Text Classifiers},
author={Dheeraj Rajagopal and Vidhisha Balachandran and Eduard Hovy and Yulia Tsvetkov},
year={2021},
eprint={2103.12279},
archivePrefix={arXiv},
primaryClass={cs.CL}
}