- Python 3.8.10
- PyTorch 1.21.1
- transformers 4.10.0
You can directly test the model through
python run_roberta_rel.py
Then you can obtain the results in the test_reuslts.txt such as
results {'disagree-f1': 0.7458323215682784, 'neutral-f1': 0.557027589856837, 'agree-f1': 0.7170068128058874, 'macro-f1': 0.6732889080770009, 'micro-f1': 0.6875956752519801, 'precision': 0.6876456876456877}
You need
python preprocess_graph.py
python train_and_extract_graph_features.py
python run_roberta_rel.py (adding --do_train to the args)
Trained model can be downloaded from : https://drive.google.com/file/d/11YSO_BOpYCDR08FyxjpX3xi7M1O2LmRK/view?usp=sharing
Dataset can be downloaded from : https://scale.com/open-av-datasets/oxford
Yun Luo, Zihan Liu, Stan Z. Li, and Yue Zhang∗. 2023. Improving (Dis)agreement Detection with Inductive Social Relation Information From Comment-Reply Interactions. In Proceedings of the ACM Web Conference 2023 (WWW ’23), May 1–5, 2023, Austin, TX, USA. ACM, New York, NY, USA, 10 pages. https://doi.org/10.1145/3543507.3583314