mmpretrain/docs/model_zoo.md

Model Zoo

ImageNet

ImageNet has multiple versions, but the most commonly used one is ILSVRC 2012. The ResNet family models below are trained by standard data augmentations, i.e., RandomResizedCrop, RandomHorizontalFlip and Normalize.

Model	Params(M)	Flops(G)	Top-1 (%)	Top-5 (%)	Config	Download
VGG-11	132.86	7.63	68.75	88.87	config	model | log
VGG-13	133.05	11.34	70.02	89.46	config	model | log
VGG-16	138.36	15.5	71.62	90.49	config	model | log
VGG-19	143.67	19.67	72.41	90.80	config	model | log
VGG-11-BN	132.87	7.64	70.75	90.12	config	model | log
VGG-13-BN	133.05	11.36	72.15	90.71	config	model | log
VGG-16-BN	138.37	15.53	73.72	91.68	config	model | log
VGG-19-BN	143.68	19.7	74.70	92.24	config	model | log
ResNet-18	11.69	1.82	70.07	89.44	config	model | log
ResNet-34	21.8	3.68	73.85	91.53	config	model | log
ResNet-50	25.56	4.12	76.55	93.15	config	model | log
ResNet-101	44.55	7.85	78.18	94.03	config	model | log
ResNet-152	60.19	11.58	78.63	94.16	config	model | log
ResNeSt-50*	27.48	5.41	81.13	95.59		model | log
ResNeSt-101*	48.28	10.27	82.32	96.24		model | log
ResNeSt-200*	70.2	17.53	82.41	96.22		model | log
ResNeSt-269*	110.93	22.58	82.70	96.28		model | log
ResNetV1D-50	25.58	4.36	77.54	93.57	config	model | log
ResNetV1D-101	44.57	8.09	78.93	94.48	config	model | log
ResNetV1D-152	60.21	11.82	79.41	94.7	config	model | log
ResNeXt-32x4d-50	25.03	4.27	77.90	93.66	config	model | log
ResNeXt-32x4d-101	44.18	8.03	78.71	94.12	config	model | log
ResNeXt-32x8d-101	88.79	16.5	79.23	94.58	config	model | log
ResNeXt-32x4d-152	59.95	11.8	78.93	94.41	config	model | log
SE-ResNet-50	28.09	4.13	77.74	93.84	config	model | log
SE-ResNet-101	49.33	7.86	78.26	94.07	config	model | log
ShuffleNetV1 1.0x (group=3)	1.87	0.146	68.13	87.81	config	model | log
ShuffleNetV2 1.0x	2.28	0.149	69.55	88.92	config	model | log
MobileNet V2	3.5	0.319	71.86	90.42	config	model | log
ViT-B/16*	86.86	33.03	84.20	97.18	config	model | log
ViT-B/32*	88.3	8.56	81.73	96.13	config	model | log
ViT-L/16*	304.72	116.68	85.08	97.38	config	model | log
ViT-L/32*	306.63	29.66	81.52	96.06	config	model | log
Swin-Transformer tiny	28.29	4.36	81.18	95.61	config	model | log
Swin-Transformer small	49.61	8.52	83.02	96.29	config	model | log
Swin-Transformer base	87.77	15.14	83.36	96.44	config	model | log
Transformer in Transformer small*	23.76	3.36	81.52	95.73	config	model | log

Models with * are converted from other repos, others are trained by ourselves.

CIFAR10

Model	Params(M)	Flops(G)	Top-1 (%)	Config	Download
ResNet-18-b16x8	11.17	0.56	94.82		config
ResNet-34-b16x8	21.28	1.16	95.34		config
ResNet-50-b16x8	23.52	1.31	95.55		config
ResNet-101-b16x8	42.51	2.52	95.58		config
ResNet-152-b16x8	58.16	3.74	95.76		config