Update ResNet50 tuning result with pytorch QAT mode
@@ -31,6 +31,7 @@ This document describes the step-by-step instructions for reproducing PyTorch Re
cd examples/pytorch/image_recognition/imagenet/cpu/QAT
python main.py -t -a resnet50 --pretrained --config /path/to/config_file /path/to/imagenet
```
+ For ResNet50 model, we can get int8 0.7614 accuracy vs fp32 0.7613.
### 2. ResNet18
