fix ResNet50 links (#2451)

PaddleCV/metric_learning/README.md

@@ -25,7 +25,7 @@ sh download_sop.sh
 
 ## Training metric learning models
 
-To train a metric learning model, one need to set the neural network as backbone and the metric loss function to optimize. You can download [ResNet50](http://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_pretrained.zip) pretrained on imagenet dataset as backbone. We train meiric learning model using softmax or arcmargin loss firstly, and then fine-turned the model using other metric learning loss, such as triplet, quadruplet and eml loss. One example of training using arcmargin loss is shown below:
+To train a metric learning model, one need to set the neural network as backbone and the metric loss function to optimize. You can download [ResNet50](http://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_pretrained.tar) pretrained on imagenet dataset as backbone. We train meiric learning model using softmax or arcmargin loss firstly, and then fine-turned the model using other metric learning loss, such as triplet, quadruplet and eml loss. One example of training using arcmargin loss is shown below:
 
 
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PaddleCV/metric_learning/README_cn.md

@@ -25,7 +25,7 @@ sh download_sop.sh
 
 ## 模型训练 
 
-为了训练度量学习模型，我们需要一个神经网络模型作为骨架模型（如[ResNet50](http://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_pretrained.zip)）和度量学习代价函数来进行优化。我们首先使用 softmax 或者 arcmargin 来进行训练，然后使用其它的代价函数来进行微调，例如：triplet，quadruplet和eml。下面是一个使用arcmargin训练的例子：
+为了训练度量学习模型，我们需要一个神经网络模型作为骨架模型（如[ResNet50](http://paddle-imagenet-models-name.bj.bcebos.com/ResNet50_pretrained.tar)）和度量学习代价函数来进行优化。我们首先使用 softmax 或者 arcmargin 来进行训练，然后使用其它的代价函数来进行微调，例如：triplet，quadruplet和eml。下面是一个使用arcmargin训练的例子：
 
 
 ```