diff --git a/docs/zh_CN/models/ViT_and_DeiT.md b/docs/zh_CN/models/ViT_and_DeiT.md index fed45b9328b31cf752b09ec9ce71833f26182f6a..51df9396cc3c120aa3ceb419d3a8ce4d70b15316 100644 --- a/docs/zh_CN/models/ViT_and_DeiT.md +++ b/docs/zh_CN/models/ViT_and_DeiT.md @@ -21,25 +21,25 @@ DeiT(Data-efficient Image Transformers)系列模型是由 FaceBook 在 2020 | Models | Top1 | Top5 | Reference
top1 | Reference
top5 | FLOPS
(G) | Params
(M) | |:--:|:--:|:--:|:--:|:--:|:--:|:--:| -| ViT_small_patch16_224 | 0.7769 | 0.9342 | 0.7785 | 0.9342 | | | -| ViT_base_patch16_224 | 0.8195 | 0.9617 | 0.8178 | 0.9613 | | | -| ViT_base_patch16_384 | 0.8414 | 0.9717 | 0.8420 | 0.9722 | | | -| ViT_base_patch32_384 | 0.8176 | 0.9613 | 0.8166 | 0.9613 | | | -| ViT_large_patch16_224 | 0.8323 | 0.9650 | 0.8306 | 0.9644 | | | -| ViT_large_patch16_384 | 0.8513 | 0.9736 | 0.8517 | 0.9736 | | | -| ViT_large_patch32_384 | 0.8153 | 0.9608 | 0.815 | - | | | +| ViT_small_patch16_224 | 0.7769 | 0.9342 | 0.7785 | 0.9342 | 9.41 | 48.60 | +| ViT_base_patch16_224 | 0.8195 | 0.9617 | 0.8178 | 0.9613 | 16.85 | 86.42 | +| ViT_base_patch16_384 | 0.8414 | 0.9717 | 0.8420 | 0.9722 | 49.35 | 86.42 | +| ViT_base_patch32_384 | 0.8176 | 0.9613 | 0.8166 | 0.9613 | 12.66 | 88.19 | +| ViT_large_patch16_224 | 0.8323 | 0.9650 | 0.8306 | 0.9644 | 59.65 | 304.12 | +| ViT_large_patch16_384 | 0.8513 | 0.9736 | 0.8517 | 0.9736 | 174.70 | 304.12 | +| ViT_large_patch32_384 | 0.8153 | 0.9608 | 0.815 | - | 44.24 | 306.48 | | Models | Top1 | Top5 | Reference
top1 | Reference
top5 | FLOPS
(G) | Params
(M) | |:--:|:--:|:--:|:--:|:--:|:--:|:--:| -| DeiT_tiny_patch16_224 | 0.718 | 0.910 | 0.722 | 0.911 | | | -| DeiT_small_patch16_224 | 0.796 | 0.949 | 0.799 | 0.950 | | | -| DeiT_base_patch16_224 | 0.817 | 0.957 | 0.818 | 0.956 | | | -| DeiT_base_patch16_384 | 0.830 | 0.962 | 0.829 | 0.972 | | | -| DeiT_tiny_distilled_patch16_224 | 0.741 | 0.918 | 0.745 | 0.919 | | | -| DeiT_small_distilled_patch16_224 | 0.809 | 0.953 | 0.812 | 0.954 | | | -| DeiT_base_distilled_patch16_224 | 0.831 | 0.964 | 0.834 | 0.965 | | | -| DeiT_base_distilled_patch16_384 | 0.851 | 0.973 | 0.852 | 0.972 | | | +| DeiT_tiny_patch16_224 | 0.718 | 0.910 | 0.722 | 0.911 | 1.07 | 5.68 | +| DeiT_small_patch16_224 | 0.796 | 0.949 | 0.799 | 0.950 | 4.24 | 21.97 | +| DeiT_base_patch16_224 | 0.817 | 0.957 | 0.818 | 0.956 | 16.85 | 86.42 | +| DeiT_base_patch16_384 | 0.830 | 0.962 | 0.829 | 0.972 | 49.35 | 86.42 | +| DeiT_tiny_distilled_patch16_224 | 0.741 | 0.918 | 0.745 | 0.919 | 1.08 | 5.87 | +| DeiT_small_distilled_patch16_224 | 0.809 | 0.953 | 0.812 | 0.954 | 4.26 | 22.36 | +| DeiT_base_distilled_patch16_224 | 0.831 | 0.964 | 0.834 | 0.965 | 16.93 | 87.18 | +| DeiT_base_distilled_patch16_384 | 0.851 | 0.973 | 0.852 | 0.972 | 49.43 | 87.18 | 关于 Params、FLOPs、Inference speed 等信息,敬请期待。