diff --git a/docs/zh_CN/algorithm_introduction/ImageNet_models.md b/docs/zh_CN/algorithm_introduction/ImageNet_models.md index 6b13bd5ae5de6b64b29d645cfc810e5f61ec58fc..402c47c06afdcefbae05c5634bf7fb060ff5946e 100644 --- a/docs/zh_CN/algorithm_introduction/ImageNet_models.md +++ b/docs/zh_CN/algorithm_introduction/ImageNet_models.md @@ -424,13 +424,13 @@ ViT(Vision Transformer) 与 DeiT(Data-efficient Image Transformers)系列模 关于 LeViT 系列模型的精度、速度指标如下表所示,更多介绍可以参考:[LeViT 系列模型文档](../models/LeViT.md)。 -| 模型 | Top-1 Acc | Top-5 Acc | time(ms)
bs=1 | time(ms)
bs=4 | FLOPs(M) | Params(M) | 下载地址 | -| ---------- | --------- | --------- | ---------------- | ---------------- | -------- | --------- | ------------------------------------------------------------ | -| LeViT_128S | 0.7598 | 0.9269 | | | 281 | 7.42 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/LeViT_128S_pretrained.pdparams) | -| LeViT_128 | 0.7810 | 0.9371 | | | 365 | 8.87 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/LeViT_128_pretrained.pdparams) | -| LeViT_192 | 0.7934 | 0.9446 | | | 597 | 10.61 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/LeViT_192_pretrained.pdparams) | -| LeViT_256 | 0.8085 | 0.9497 | | | 1049 | 18.45 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/LeViT_256_pretrained.pdparams) | -| LeViT_384 | 0.8191 | 0.9551 | | | 2234 | 38.45 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/LeViT_384_pretrained.pdparams) | +| 模型 | Top-1 Acc | Top-5 Acc | time(ms)
bs=1 | time(ms)
bs=4 | FLOPs(M) | Params(M) | 预训练模型下载地址 | inference模型下载地址 | +| ---------- | --------- | --------- | ---------------- | ---------------- | -------- | --------- | ------------------------------------------------------------ | ------------------------------------------------------------ | +| LeViT_128S | 0.7598 | 0.9269 | | | 281 | 7.42 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/LeViT_128S_pretrained.pdparams) | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/eViT_128S_infer.tar) | +| LeViT_128 | 0.7810 | 0.9371 | | | 365 | 8.87 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/LeViT_128_pretrained.pdparams) | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/LeViT_128_infer.tar) | +| LeViT_192 | 0.7934 | 0.9446 | | | 597 | 10.61 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/LeViT_192_pretrained.pdparams) | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/LeViT_192_infer.tar) | +| LeViT_256 | 0.8085 | 0.9497 | | | 1049 | 18.45 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/LeViT_256_pretrained.pdparams) | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/LeViT_256_infer.tar) | +| LeViT_384 | 0.8191 | 0.9551 | | | 2234 | 38.45 | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/LeViT_384_pretrained.pdparams) | [下载链接](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/inference/LeViT_384_infer.tar) | **注**:与 Reference 的精度差异源于数据预处理不同及未使用蒸馏的 head 作为输出。