diff --git a/demo/word2vec/api_train_v2.py b/demo/word2vec/api_train_v2.py
index eb61a7250fb84846222d95b7a7722441ad31c924..604adba192ee23aff4359df03d9f5e0ce21b8cde 100644
--- a/demo/word2vec/api_train_v2.py
+++ b/demo/word2vec/api_train_v2.py
@@ -69,6 +69,7 @@ def main():
     def event_handler(event):
         if isinstance(event, paddle.event.EndIteration):
             if event.batch_id % 100 == 0:
+                trainer.save_parameter("output", "batch-" + str(event.batch_id))
                 result = trainer.test(
                     paddle.batch(
                         paddle.dataset.imikolov.test(word_dict, N), 32))
diff --git a/python/paddle/v2/trainer.py b/python/paddle/v2/trainer.py
index 552c6690a608f4cc247fa9d5f774e965cec1f97c..028f25a04676825a51530510abc579d48d2cbf4e 100644
--- a/python/paddle/v2/trainer.py
+++ b/python/paddle/v2/trainer.py
@@ -1,4 +1,6 @@
 import collections
+import gzip
+import os
 
 import py_paddle.swig_paddle as api
 
@@ -96,6 +98,18 @@ class SGD(object):
             self.__gradient_machine__.prefetch(in_args)
             self.__parameter_updater__.getParametersRemote()
 
+    def save_parameter(self, dir_name, file_name):
+        if not os.path.exists(dir_name):
+            os.makedirs(dir_name)
+        param_file_name = dir_name + "/" + file_name + '.tar.gz'
+        assert not os.path.exists(param_file_name)
+        self.__parameter_updater__.catchUpWith()
+        self.__parameter_updater__.apply()
+        self.__parameter_updater__.getParametersRemote(True, True)
+        with gzip.open(param_file_name, 'w') as f:
+            self.__parameters__.to_tar(f)
+        self.__parameter_updater__.restore()
+
     def train(self, reader, num_passes=1, event_handler=None, feeding=None):
         """
         Training method. Will train num_passes of input data.