Update README.md

README.md

@@ -25,12 +25,8 @@ The linear module **bert.encoder.layer.9.output.dense, bert.encoder.layer.10.out
 
 ### Test result
 
-- Batch size = 8
-- [Amazon Web Services](https://aws.amazon.com/) c6i.xlarge (Intel ICE Lake: 4 vCPUs, 8g Memory) instance.
-
 |   |INT8|FP32|
 |---|:---:|:---:|
-| **Throughput (samples/sec)**  |23.986|11.202|
 | **Accuracy (eval-f1)** |0.8997|0.9042|
 | **Model size (MB)**  |120|418|
 
@@ -42,6 +38,3 @@ int8_model = OptimizedModel.from_pretrained(
     'Intel/bert-base-uncased-mrpc-int8-static',
 )
 ```
-
-Notes:  
- - The INT8 model has better performance than the FP32 model when the CPU is fully occupied. Otherwise, there will be the illusion that INT8 is inferior to FP32.