00_basics

Basic GNN training

This experiment demonstrates the following steps of working with GNN within the GNN-AID framework:

1. Loading the dataset and preparing the data.
2. Building the GNN model.
3. Training the GNN model.
4. Saving and loading the model weights.
5. Assessing the quality of the trained model.

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Folder contents

• train_gnn.py — script for training GNN.
• run_example.sh — script for running the experiment.
• README.md — description of the experiment.

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Quick start

Run:

  bash run_example.sh

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Example of the experimental result

Metric	Value
F1 (macro, test)	~0.83
Accuracy (test)	~0.85

The exact values may differ due to random weight initialization and model training process.