diff --git a/README.md b/README.md
index 864cabb2..c5d83f3c 100644
--- a/README.md
+++ b/README.md
@@ -176,7 +176,7 @@ optimizer.summary()
 The output of `optimizer.summary()` will be something like:
 ```
  -------------------------------- ---------------------- -------------- ----------------------
-|             method             |        status        | latency(ms)  |       accuracy       |
+|             method             |        status        | latency(ms)  |     metric value     |
  -------------------------------- ---------------------- -------------- ----------------------
 |            original            |      successful      |    45.145    |        0.975         |
 |              bf16              |      successful      |    27.549    |        0.975         |
@@ -190,7 +190,7 @@ The output of `optimizer.summary()` will be something like:
 |        onnxruntime_fp32        |      successful      |    20.838    |        0.975*        |
 |    onnxruntime_int8_qlinear    |      successful      |    7.123     |        0.981         |
  -------------------------------- ---------------------- -------------- ----------------------
-* means we assume the precision of the traced model does not change, so we don't recompute accuracy to save time.
+* means we assume the metric value of the traced model does not change, so we don't recompute metric value to save time.
 Optimization cost 60.8s in total.
 ```
 
diff --git a/docs/readthedocs/source/doc/Nano/Overview/pytorch_inference.md b/docs/readthedocs/source/doc/Nano/Overview/pytorch_inference.md
index c1f916f9..a2646aa7 100644
--- a/docs/readthedocs/source/doc/Nano/Overview/pytorch_inference.md
+++ b/docs/readthedocs/source/doc/Nano/Overview/pytorch_inference.md
@@ -284,7 +284,6 @@ The output table of `optimize()` looks like:
 |        onnxruntime_fp32        |      successful      |    3.801     |
 |    onnxruntime_int8_qlinear    |      successful      |    4.727     |
  -------------------------------- ---------------------- --------------
-* means we assume the accuracy of the traced model does not change, so we don't recompute accuracy to save time.
 Optimization cost 58.3s in total.
 ```