Update README.md

example/auto_compression/detection/README.md

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 | 模型  | Base mAP | 离线量化mAP | ACT量化mAP | TRT-FP32 | TRT-FP16 | TRT-INT8 |  配置文件 | 量化模型  |
 | :-------- |:-------- |:--------: | :---------------------: | :----------------: | :----------------: | :---------------: | :----------------------: | :---------------------: |
 | PP-YOLOE-l | 50.9  |  - | 50.6  |   11.2ms  |   7.7ms   |  **6.7ms**  |  [config](https://github.com/PaddlePaddle/PaddleSlim/tree/develop/demo/auto_compression/detection/configs/ppyoloe_l_qat_dis.yaml) | [Model](https://bj.bcebos.com/v1/paddle-slim-models/act/ppyoloe_crn_l_300e_coco_quant.tar) |
-| PP-YOLOE-s |  43.1  |   26.2 |   42.6   |   6.51ms  |   2.77ms   |  **2.12ms**  |  [config](https://github.com/PaddlePaddle/PaddleSlim/tree/develop/demo/auto_compression/detection/configs/ppyoloe_s_qat_dis.yaml) | [Model](https://bj.bcebos.com/v1/paddle-slim-models/act/ppyoloe_s_quant.tar) |
+| PP-YOLOE-s |  43.1  |   41.2 |   42.6   |   6.51ms  |   2.77ms   |  **2.12ms**  |  [config](https://github.com/PaddlePaddle/PaddleSlim/tree/develop/demo/auto_compression/detection/configs/ppyoloe_s_qat_dis.yaml) | [Model](https://bj.bcebos.com/v1/paddle-slim-models/act/ppyoloe_s_quant.tar) |
 
 - mAP的指标均在COCO val2017数据集中评测得到，IoU=0.5:0.95。
 - PP-YOLOE-l模型在Tesla V100的GPU环境下测试，并且开启TensorRT，batch_size=1，包含NMS，测试脚本是[benchmark demo](https://github.com/PaddlePaddle/PaddleDetection/tree/release/2.4/deploy/python)。