diff --git a/src/common/common.h b/src/common/common.h
index d8adadae3..aaf2b8a37 100644
--- a/src/common/common.h
+++ b/src/common/common.h
@@ -26,6 +26,15 @@ inline std::vector<std::string> Split(const std::string& s, char delim) {
   }
   return ret;
 }
+
+// simple routine to convert any data to string
+template<typename T>
+inline std::string ToString(const T& data) {
+  std::ostringstream os;
+  os << data;
+  return os.str();
+}
+
 }  // namespace common
 }  // namespace xgboost
 #endif  // XGBOOST_COMMON_COMMON_H_
diff --git a/src/gbm/gbtree.cc b/src/gbm/gbtree.cc
index 29fb114a6..7e58a060a 100644
--- a/src/gbm/gbtree.cc
+++ b/src/gbm/gbtree.cc
@@ -126,6 +126,9 @@ class GBTree : public GradientBooster {
       CHECK_EQ(fi->Read(dmlc::BeginPtr(tree_info), sizeof(int) * mparam.num_trees),
                sizeof(int) * mparam.num_trees);
     }
+    this->cfg.clear();
+    this->cfg.push_back(std::make_pair(std::string("num_feature"),
+                                       common::ToString(mparam.num_feature)));
     // clear the predict buffer.
     this->ResetPredBuffer(num_pbuffer);
   }
diff --git a/src/learner.cc b/src/learner.cc
index 59f7c53f7..5d00496ef 100644
--- a/src/learner.cc
+++ b/src/learner.cc
@@ -14,6 +14,7 @@
 #include <limits>
 #include <iomanip>
 #include "./common/io.h"
+#include "./common/common.h"
 #include "./common/random.h"
 
 namespace xgboost {
@@ -27,13 +28,6 @@ Learner::Dump2Text(const FeatureMap& fmap, int option) const {
   return gbm_->Dump2Text(fmap, option);
 }
 
-// simple routine to convert any data to string
-template<typename T>
-inline std::string ToString(const T& data) {
-  std::ostringstream os;
-  os << data;
-  return os.str();
-}
 
 /*! \brief training parameter for regression */
 struct LearnerModelParam
@@ -192,7 +186,7 @@ class LearnerImpl : public Learner {
     common::GlobalRandom().seed(tparam.seed);
 
     // set number of features correctly.
-    cfg_["num_feature"] = ToString(mparam.num_feature);
+    cfg_["num_feature"] = common::ToString(mparam.num_feature);
     if (gbm_.get() != nullptr) {
       gbm_->Configure(cfg_.begin(), cfg_.end());
     }
@@ -252,13 +246,13 @@ class LearnerImpl : public Learner {
       attributes_ = std::map<std::string, std::string>(
           attr.begin(), attr.end());
     }
-
     if (metrics_.size() == 0) {
       metrics_.emplace_back(Metric::Create(obj_->DefaultEvalMetric()));
     }
     this->base_score_ = mparam.base_score;
     gbm_->ResetPredBuffer(pred_buffer_size_);
-    cfg_["num_class"] = ToString(mparam.num_class);
+    cfg_["num_class"] = common::ToString(mparam.num_class);
+    cfg_["num_feature"] = common::ToString(mparam.num_feature);
     obj_->Configure(cfg_.begin(), cfg_.end());
   }
 
@@ -395,7 +389,7 @@ class LearnerImpl : public Learner {
     }
 
     // setup
-    cfg_["num_feature"] = ToString(mparam.num_feature);
+    cfg_["num_feature"] = common::ToString(mparam.num_feature);
     CHECK(obj_.get() == nullptr && gbm_.get() == nullptr);
     obj_.reset(ObjFunction::Create(name_obj_));
     gbm_.reset(GradientBooster::Create(name_gbm_));