nli_explain

Explain BERT model's decision in NLI task.

Description

This repository contains various methods and attempts of explaining BERT model's decision during Natural Language Inference (NLI) task with Feature Interaction methods. This contains:

• IH - integrated Hessians
• Archipelago
• X-Archipelago (ours) - cross-sentence version (for NLI examples with two sentences) of Archipelgo
• MAFIA (ours) - MAsk-based Feature Interaction Attribution

requirements

nltk
pandas
numpy
torch
transformers

How to Use

1. download e-SNLI dataset from https://github.com/OanaMariaCamburu/e-SNLI/tree/master/dataset. Put the files in data/ folder.
2. preprocess data by python prepare_data.py.
3. For each explainer (lime, IH, Arch (Archipelago), Mask (MAFIA)), you can find a script in scripts/ folder. It will create a .json file containing explanation for each NLI example in the explanations/ directory (created if not already).

• for details, check explainers/save_explanations.py.
• for implementation of each explainer, check explainers/ directory.

4. For evaluation, checkout the scripts/eval_explanation.sh script. The template function and example usage are shown here. Modify the file according to your needs.