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PyTorch implementation of NovoGrad

Install

pip install novograd

Notice

When using NovoGrad, learning rate scheduler play an important role. Do not forget to set it.

Performance

MNIST

Under Trained 3 epochs, same Architecture Neural Netwrok.

Test Acc(%) lr lr scheduler beta1 beta2 weight decay
Momentum SGD 96.92 0.01 None 0.9 N/A 0.001
Adam 96.72 0.001 None 0.9 0.999 0.001
AdamW 97.34 0.001 None 0.9 0.999 0.001
NovoGrad 97.55 0.01 cosine 0.95 0.98 0.001

Refference

Boris Ginsburg, Patrice Castonguay, Oleksii Hrinchuk, Oleksii Kuchaiev, Vitaly Lavrukhin, Ryan Leary, Jason Li, Huyen Nguyen, Jonathan M. Cohen, Stochastic Gradient Methods with Layer-wise Adaptive Moments for Training of Deep Networks, arXiv:1905.11286 [cs.LG], https://arxiv.org/pdf/1905.11286.pdf

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PyTorch implementation of NovoGrad

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