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Graph-Based-Text-Classification

This code is for our proposed model in DL-NLP course. See proposed model here

  • Steps to run this model:
  1. Datasets of MR, SST-2, R8 and 20ng should be put under Data/ and path needs to be updated in config.py file.
  2. For parameter tuning, use config.py file and change parameters.
  3. python3 train.py

Baselines:

  • TF-IDF with Logistic Regression:TF-IDF + LR
  • LSTM with pre-trained GloVe embeddings(d=300) : LSTM - GloVe
  • Code for TGCN and VGCN-BERT: adjacency.ipynb + gcn.py + train.py

Dataset Statistics:

Dataset Statistics

Results:

results

Project Report- Final_Project_Report.pdf