Implementation of Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets

Running train.py with default arguments will run my best (yet) attempt to reproduce the "Grokking" behavior on modular division as seen in Figure 1 of the paper.

python train.py

The results seem highly sensitive to optimizer hyperparameter selection, and I have not yet tried all of the configurations outlined in the paper.

@inproceedings{power2021grokking,
  title={Grokking: Generalization beyond overfitting on small algorithmic datasets},
  author={Power, Alethea and Burda, Yuri and Edwards, Harri and Babuschkin, Igor and Misra, Vedant},
  booktitle={ICLR MATH-AI Workshop},
  year={2021}
}