WebbTable 3: Classification accuracies and training speed on the CIFAR-10 and CIFAR-100 datasets. The numbers in parentheses (·) indicate the ratio of the training speed w.r.t. the vanilla base optimizer’s (SGD’s) speed. Green indicates improvement compared to SAM, whereas red suggests a degradation. - "Sharpness-Aware Training for Free" WebbWe propose the Sharpness-Aware training for Free (SAF) algorithm to penalize the trajectory loss for sharpness-aware training. More importantly, SAF requires almost zero …

Towards Efficient and Scalable Sharpness-Aware Minimization

WebbNext, we introduce the Sharpness-Aware Training for Free (SAF) algorithm whose pseudocode can be found in Algorithm 1. We first start with recalling SAM’s sharpness measure loss. Then we explain the intuition for the trajectory loss as a substitute for SAM’s sharpness measure loss in Section 3.1. Webb21 nov. 2024 · This work introduces a novel, effective procedure for simultaneously minimizing loss value and loss sharpness, Sharpness-Aware Minimization (SAM), which improves model generalization across a variety of benchmark datasets and models, yielding novel state-of-the-art performance for several. 451 Highly Influential PDF rayus radiology layton

Sharpness-Aware Training for Free Papers With Code

Webb4 nov. 2024 · The sharpness of loss function can be defined as the difference between the maximum training loss in an ℓ p ball with a fixed radius ρ. and the training loss at w. The paper [1] shows the tendency that a sharp minimum has a larger generalization gap than a flat minimum does. WebbThe Sharpness Measure is defined as Objective:To find a “cheaper” replacement of the sharpness measure. where where is the past trajectory of the weights Then •Now, we … WebbSharpness-Aware Training for Free Jiawei Du1 ;2, Daquan Zhou 3, Jiashi Feng , Vincent Y. F. Tan4;2, Joey Tianyi Zhou1 1Centre for Frontier AI Research (CFAR), A*STAR, … rayus radiology leadership