Update README.md (#13114)

* Update README.md

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

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* Update README.zh-CN.md

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>

README.zh-CN.md

@@ -358,8 +358,8 @@ YOLOv5 [release v6.2](https://github.com/ultralytics/yolov5/releases) 带来对
 - **准确性**都在单模型单尺度上计算，数据集使用 [ImageNet-1k](https://www.image-net.org/index.php) 。<br>复现命令 `python classify/val.py --data ../datasets/imagenet --img 224`
 - **推理速度**是使用 100 个推理图像进行平均得到，测试环境使用谷歌 [Colab Pro](https://colab.research.google.com/signup) V100 高 RAM 实例。<br>复现命令 `python classify/val.py --data ../datasets/imagenet --img 224 --batch 1`
 - **模型导出**到 FP32 的 ONNX 和 FP16 的 TensorRT 使用 `export.py` 。<br>复现命令 `python export.py --weights yolov5s-cls.pt --include engine onnx --imgsz 224`
-  </details>
-  </details>
+</details>
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 <details>
   <summary>分类训练示例 &nbsp;<a href="https://colab.research.google.com/github/ultralytics/yolov5/blob/master/classify/tutorial.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a></summary>