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V0.2.7-RSB-A3-ImageNet-Weights
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@Lupin1998 Lupin1998 released this 26 Feb 19:17
· 63 commits to main since this release
rsb-a3-weights
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A collection of weights and logs for image classification experiments with RSB A3 training setting on ImageNet-1K (download). You can view the training setting in ResNet strikes back and find the full results in MogaNet (Appendix Table A.7). You can download all files from Baidu Cloud (ss3j).

  • We train all models for 100 epochs according to the RSB A3 setting on ImageNet-1K. We turn the basic learning in {8e-3, 6e-3} to get better performances.
  • The best top-1 accuracy of image classification in the last 10 training epochs is reported for all experiments.

RSB A3 Image Classification on ImageNet-1K

Model Date Train / Test Params (M) Top-1 (%) Top-5 (%) Config Download
ResNet-50 CVPR'2016 160 / 224 26 78.1 93.8 config model | log
ResNet-101 CVPR'2016 160 / 224 45 79.9 94.9 config model | log
ResNet-152 CVPR'2016 160 / 224 60 80.7 95.2 config model | log
ViT-T ICLR'2021 160 / 224 6 66.7 87.7 config model | log
ViT-S ICLR'2021 160 / 224 22 73.8 91.2 config model | log
ViT-B ICLR'2021 160 / 224 87 76.0 91.8 config model | log
PVT-T ICCV'2021 160 / 224 13 71.5 89.8 config model | log
PVT-S ICCV'2021 160 / 224 25 72.1 90.2 config model | log
Swin-T ICCV'2021 160 / 224 28 77.7 93.7 config model | log
Swin-S ICCV'2021 160 / 224 50 80.2 95.1 config model | log
Swin-B ICCV'2021 160 / 224 50 80.5 95.4 config model | log
LITV2-T NIPS'2022 160 / 224 28 79.7 94.7 config model | log
LITV2-M NIPS'2022 160 / 224 49 80.5 95.2 config model | log
LITV2-B NIPS'2022 160 / 224 87 81.3 95.5 config model | log
ConvMixer-768-d32 arXiv'2022 160 / 224 21 77.6 93.5 config model | log
PoolFormer-S12 CVPR'2022 160 / 224 12 69.3 88.7 config model | log
PoolFormer-S24 CVPR'2022 160 / 224 21 74.1 91.8 config model | log
PoolFormer-S36 CVPR'2022 160 / 224 31 74.6 92.0 config model | log
PoolFormer-M36 CVPR'2022 160 / 224 56 80.7 95.2 config model | log
PoolFormer-M48 CVPR'2022 160 / 224 73 81.2 95.3 config model | log
ConvNeXt-T CVPR'2022 160 / 224 29 78.8 94.2 config model | log
ConvNeXt-S CVPR'2022 160 / 224 50 81.7 95.7 config model | log
ConvNeXt-B CVPR'2022 160 / 224 89 82.1 95.9 config model | log
ConvNeXt-L CVPR'2022 160 / 224 189 82.8 96.0 config model | log
VAN-B0 arXiv'2022 160 / 224 4 72.6 94.2 config model | log
VAN-B2 arXiv'2022 160 / 224 27 81.0 91.5 config model | log
VAN-B3 arXiv'2022 160 / 224 45 81.9 95.7 config model | log
HorNet-T (7×7) NIPS'2022 160 / 224 22 80.1 95.0 config model | log
HorNet-S (7×7) NIPS'2022 160 / 224 50 81.2 95.4 config model | log
MogaNet-XT arXiv'2022 160 / 224 3 72.8 91.3 config model | log
MogaNet-T arXiv'2022 160 / 224 5 75.4 92.6 config model | log
MogaNet-S arXiv'2022 160 / 224 25 81.1 95.5 config model | log
MogaNet-B arXiv'2022 160 / 224 44 82.2 95.9 config model | log
MogaNet-L arXiv'2022 160 / 224 83 83.2 96.4 config model | log
Assets 60
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