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mmclassification/docs/model_zoo.md
whcao 3be95b99c2
[Feature]Modify modelzoo readme (#230) 
* add mytrain.py for test

* test before layers

* test attr in layers

* test classifier

* delete mytrain.py

* add imagenet_bs4096_AdamW.py

* delete 2 lines of comments

* change bs to 64

* fix bug

* add vit to model_zoo.md

* rename
2021-04-29 15:18:55 +08:00

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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 77.4 93.66 config model | log
ResNetV1D-101 44.57 8.09 78.85 94.38 config model | log
ResNetV1D-152 60.21 11.82 79.35 94.61 config model | log
ResNeXt-32x4d-50 25.03 4.27 77.92 93.74 config model | log
ResNeXt-32x4d-101 44.18 8.03 78.7 94.34 config model | log
ResNeXt-32x8d-101 88.79 16.5 79.22 94.52 config model | log
ResNeXt-32x4d-152 59.95 11.8 79.06 94.47 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

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 94.72 config model | log
ResNet-34-b16x8 21.28 1.16 95.34 config model | log
ResNet-50-b16x8 23.52 1.31 95.36 config model | log
ResNet-101-b16x8 42.51 2.52 95.66 config model | log
ResNet-152-b16x8 58.16 3.74 95.96 config model | log