README.md

metadata

license: mit
library_name: pytorch
tags:
  - graphconv
  - citeseer
  - node-classification
  - graph-neural-network

GRAPHCONV Node Classification on Citeseer

Model Details

• Architecture: GRAPHCONV
• Dataset: Citeseer
• Task: Node Classification

Usage

from src.prediction import Predictor

# Load model
predictor = Predictor.from_checkpoint("best_model.pt")

# Make predictions
result = predictor.predict(graph_data)
print(f"Predictions: {result.predictions}")
print(f"Confidence: {result.confidence}")

Files

• best_model.pt - Trained model checkpoint
• hyperparameters.json - Training configuration
• experiment_summary.json - Final metrics

Training

python scripts/train.py \
    --dataset citeseer \
    --model graphconv \
    --epochs 150 \
    --lr_scheduler