diff --git a/demo/image_classification/train.sh b/demo/image_classification/train.sh
index ed9b5220fff6a434cd332f0972d39c4149b3ebfe..db0a057bf35b4ad04a08a1e3f1fad3bd6a486350 100755
--- a/demo/image_classification/train.sh
+++ b/demo/image_classification/train.sh
@@ -24,7 +24,7 @@ paddle train \
 --test_all_data_in_one_period=1 \
 --use_gpu=1 \
 --trainer_count=1 \
---num_passes=200 \
+--num_passes=300 \
 --save_dir=$output \
 2>&1 | tee $log
 
diff --git a/demo/semantic_role_labeling/predict.sh b/demo/semantic_role_labeling/predict.sh
index a545b9a5d591b41bdbd54905cbbffc410abc8fb0..111eea95a22d33925f378114b301d3dd3cc54fa0 100644
--- a/demo/semantic_role_labeling/predict.sh
+++ b/demo/semantic_role_labeling/predict.sh
@@ -18,7 +18,7 @@ set -e
 function get_best_pass() {
   cat $1  | grep -Pzo 'Test .*\n.*pass-.*' | \
   sed  -r 'N;s/Test.* cost=([0-9]+\.[0-9]+).*\n.*pass-([0-9]+)/\1 \2/g' | \
-  sort | head -n 1
+  sort -n | head -n 1
 }   
 
 log=train.log
@@ -26,7 +26,6 @@ LOG=`get_best_pass $log`
 LOG=(${LOG})
 best_model_path="output/pass-${LOG[1]}"
 
-
 config_file=db_lstm.py
 dict_file=./data/src.dict
 label_file=./data/tgt.dict 
diff --git a/demo/semantic_role_labeling/test.sh b/demo/semantic_role_labeling/test.sh
index 844649e8c0f6867dc0766e4ec6f250c5a4a004d9..f9e1bdcd4c752474329d36c4de3378f7d58e7b4b 100644
--- a/demo/semantic_role_labeling/test.sh
+++ b/demo/semantic_role_labeling/test.sh
@@ -18,7 +18,7 @@ set -e
 function get_best_pass() {
   cat $1  | grep -Pzo 'Test .*\n.*pass-.*' | \
   sed  -r 'N;s/Test.* cost=([0-9]+\.[0-9]+).*\n.*pass-([0-9]+)/\1 \2/g' |\
-  sort | head -n 1
+  sort -n | head -n 1
 }
 
 log=train.log
@@ -36,4 +36,5 @@ paddle train \
   --job=test \
   --use_gpu=false \
   --config_args=is_test=1 \
+  --test_all_data_in_one_period=1 \
 2>&1 | tee 'test.log'
diff --git a/demo/sentiment/test.sh b/demo/sentiment/test.sh
index 098fbb91389b89c8b69ccf2f5d308e4e715ac950..c8b12a0e89dbddea56b4ee069ebf66f8d8630615 100755
--- a/demo/sentiment/test.sh
+++ b/demo/sentiment/test.sh
@@ -17,7 +17,7 @@ set -e
 function get_best_pass() {
   cat $1  | grep -Pzo 'Test .*\n.*pass-.*' | \
   sed  -r 'N;s/Test.* classification_error_evaluator=([0-9]+\.[0-9]+).*\n.*pass-([0-9]+)/\1 \2/g' |\
-  sort | head -n 1
+  sort -n | head -n 1
 }
 
 log=train.log
diff --git a/doc/demo/quick_start/index_en.md b/doc/demo/quick_start/index_en.md
index e7d74512292c89233373c48d05895794d56702d8..659485d9be1b6a3e9759a2fd040cb09d1f2a3005 100644
--- a/doc/demo/quick_start/index_en.md
+++ b/doc/demo/quick_start/index_en.md
@@ -1,4 +1,4 @@
-# Quick Start Tutorial
+# Quick Start
 
 This tutorial will teach the basics of deep learning (DL), including how to implement many different models in PaddlePaddle. You will learn how to:
   - Prepare data into the standardized format that PaddlePaddle accepts.
@@ -477,7 +477,7 @@ The scripts of data downloading, network configurations, and training scrips are
 <td class="left">Word embedding</td>
 <td class="left"> 15MB </td>
 <td class="left"> 8.484%</td>
-<td class="left">trainer_config.bow.py</td>
+<td class="left">trainer_config.emb.py</td>
 </tr>
 
 <tr>