MsdBert

This repository is an implementation for the paper "Modeling Intra and Inter-modality Incongruity for Multi-Modal Sarcasm Detection" that is published at the Findings of EMNLP-2020. https://www.aclweb.org/anthology/2020.findings-emnlp.124.pdf

How to use?

Envs

torchvision==0.7.0+cu101
numpy==1.18.5
transformers==3.2.0
tqdm==4.49.0
wordninja==2.0.0
torch==1.6.0+cu101
Pillow==8.0.1
scikit_learn==0.24.0

Install

pip3 install -r requirements.txt

Dataset

You can find the Image data from https://github.com/headacheboy/data-of-multimodal-sarcasm-detection.

Put the images under a folder named "Images"

Train and Test

Train:

python run_classifier.py --data_dir ./data/ --image_dir ./images/ --output_dir ./output/MsdBERT_output/  --do_train --do_test --model_select MsdBERT

Test:

python run_classifier.py --data_dir ./data/ --image_dir ./images/ --output_dir ./output/MsdBERT_output/  --do_test --model_select MsdBERT

Run all models recursively:

sh run_classifier.sh

Saving

All the models and evaluation results will be saved under the "output" folder.

Citation

@inproceedings{DBLP:conf/emnlp/PanL0Q020,
  author    = {Hongliang Pan and
               Zheng Lin and
               Peng Fu and
               Yatao Qi and
               Weiping Wang},
  title     = {Modeling Intra and Inter-modality Incongruity for Multi-Modal Sarcasm
               Detection},
  booktitle = {Proceedings of the 2020 Conference on Empirical Methods in Natural
               Language Processing: Findings, {EMNLP} 2020, Online Event, 16-20 November
               2020},
  pages     = {1383--1392},
  publisher = {Association for Computational Linguistics}
}