GNAM-RFF/run_node_experiments.sh at main · FujitsuResearch/GNAM-RFF · GitHub

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#!/bin/bash

# Run node classification experiments with hyperparameters from Appendix C.1 (Table 3)
# Use the hgt conda environment
PYTHON="\path\to\your\conda\envs\python.exe"

# Cora
echo "Training on Cora..."
$PYTHON scripts/train_node.py \
  --dataset cora \
  --cuda 2 \
  --lr 0.1 \
  --weight_decay 5e-4 \
  --M 100 \
  --R 7 \
  --theta 2.0 \
  --epochs 1000 \
  --save_model

# Citeseer - Commented out
# echo "Training on Citeseer..."
# $PYTHON scripts/train_node.py \
#   --dataset citeseer \
#   --cuda 0 \
#   --lr 0.1 \
#   --weight_decay 5e-4 \
#   --M 100 \
#   --R 5 \
#   --theta 2.5 \
#   --epochs 1000 \
#   --save_model

# Pubmed - Commented out
# echo "Training on Pubmed..."
# $PYTHON scripts/train_node.py \
#   --dataset pubmed \
#   --cuda 0 \
#   --lr 0.1 \
#   --weight_decay 5e-4 \
#   --M 100 \
#   --R 5 \
#   --theta 3.8 \
#   --epochs 1000 \
#   --save_model

# Cornell - M=100, R=6, Θ=2.9, Lr=7.3e-2, Wd=3.7e-4
# echo "Training on Cornell..."
# $PYTHON scripts/train_node.py \
#   --dataset cornell \
#   --cuda 0 \
#   --lr 7.3e-2 \
#   --weight_decay 3.7e-4 \
#   --M 100 \
#   --R 6 \
#   --theta 2.9 \
#   --epochs 1000 \
#   --save_model

echo "All experiments completed!"