udate README

examples/classification/README.md

@@ -74,5 +74,6 @@ python evaluate.py
 The evaluation results are as follows:
 
 ```
+data num: 1200
 precision: 0.956666666667, recall: 0.949013157895, f1: 0.95688225039
 ```

examples/matching/README.md

@@ -81,5 +81,6 @@ python evaluate.py
 The evaluation results are as follows:
 
 ```
+data_num: 4300
 precision: 0.857906976744, recall: 0.824249846908, f1: 0.81501664653
 ```

examples/predict/README.md

@@ -71,8 +71,9 @@ Once you have the prediction, you can run the evaluation script to evaluate the
 python evaluate.py
 ```
 
-The evaluation results are as follows:  (need to update)
+The evaluation results are as follows:
 
 ```
-precision: 0.956666666667, recall: 0.949013157895, f1: 0.95688225039
+data num: 1200
+precision: 0.494166666667, recall: 0.0444078947368, f1: 0.0816944009455
 ```