VGNets Weights

Model	Params(M)	FLOPS(M)	Top-1	Top-5
VGNetG-1.0MP	0.999	144	68.128	88.312
VGNetG-1.0MP + SE	1.143	145	70.122	89.524
VGNetG-1.5MP	1.502	191	70.494	89.684
VGNetG-1.5MP + SE	1.702	192	72.422	90.664
VGNetG-2.0MP	2.006	304	72.314	90.730
VGNetG-2.0MP + SE	2.345	306	74.324	91.788
VGNetG-2.5MP	2.493	399	73.740	91.516
VGNetG-2.5MP + SE	2.940	401	75.590	92.568

Training

Procedure
learning rate	0.2
batch size	512
weight decay	1e-4
no bias & bn decay	True
lr scheduler	cosine
min lr	1e-6
optimizer	SGD with momentum 0.9
warmup epochs	5
lable smoothing	0.1
mixup	-
cutmix	-
amp	True
image processing	RandomResizedCrop/RandomHorizontalFlip
data augment	-
dropout rate	0.0
drop path rate	-
crop size	192
val-resize size	232
val-resize size	224