diff --git a/mnist_2.prj b/mnist_2.prj
index 4c60814..d4a9150 100644
--- a/mnist_2.prj
+++ b/mnist_2.prj
@@ -18,80 +18,11 @@
                   "learningRate" : 0.10000000000000001,
                   "momentum" : 0.5,
                   "numGibbs" : 1,
-                  "weightDecay" : 0,
-                  "weightInit" : 0.01
-               }
+                  "weightDecay" : 0
+               },
+               "weightInit" : 0.01
             },
             "weights_file" : "Layer.0.weights.dat"
-         },
-         {
-            "id" : 1,
-            "name" : "Layer",
-            "numHidden" : 128,
-            "numVisibleX" : 256,
-            "numVisibleY" : 1,
-            "rbm" : {
-               "numHidden" : 128,
-               "numVisible" : 256,
-               "params" : {
-                  "doRaoBlackwell" : 1,
-                  "doSampleBatch" : 0,
-                  "gibbsDoSampleHidden" : 1,
-                  "gibbsDoSampleVisible" : 0,
-                  "learningRate" : 0.10000000000000001,
-                  "momentum" : 0.5,
-                  "numGibbs" : 1,
-                  "weightDecay" : 0,
-                  "weightInit" : 0.01
-               }
-            },
-            "weights_file" : "Layer.1.weights.dat"
-         },
-         {
-            "id" : 2,
-            "name" : "Layer",
-            "numHidden" : 64,
-            "numVisibleX" : 128,
-            "numVisibleY" : 1,
-            "rbm" : {
-               "numHidden" : 64,
-               "numVisible" : 128,
-               "params" : {
-                  "doRaoBlackwell" : 1,
-                  "doSampleBatch" : 0,
-                  "gibbsDoSampleHidden" : 1,
-                  "gibbsDoSampleVisible" : 0,
-                  "learningRate" : 0.10000000000000001,
-                  "momentum" : 0.5,
-                  "numGibbs" : 1,
-                  "weightDecay" : 0,
-                  "weightInit" : 0.01
-               }
-            },
-            "weights_file" : "Layer.2.weights.dat"
-         },
-         {
-            "id" : 3,
-            "name" : "Layer",
-            "numHidden" : 32,
-            "numVisibleX" : 64,
-            "numVisibleY" : 1,
-            "rbm" : {
-               "numHidden" : 32,
-               "numVisible" : 64,
-               "params" : {
-                  "doRaoBlackwell" : 1,
-                  "doSampleBatch" : 0,
-                  "gibbsDoSampleHidden" : 1,
-                  "gibbsDoSampleVisible" : 0,
-                  "learningRate" : 0.10000000000000001,
-                  "momentum" : 0.5,
-                  "numGibbs" : 1,
-                  "weightDecay" : 0,
-                  "weightInit" : 0.01
-               }
-            },
-            "weights_file" : "Layer.3.weights.dat"
          }
       ],
       "name" : "mnist_2"
diff --git a/source/Rbm.cpp b/source/Rbm.cpp
index c24fb19..3f809f7 100644
--- a/source/Rbm.cpp
+++ b/source/Rbm.cpp
@@ -13,13 +13,14 @@
 
 #include "Rbm.hpp"
 
-Rbm::Rbm(size_t numVisible, size_t numHidden)
+Rbm::Rbm(size_t numVisible, size_t numHidden, double weightInit)
 : m_params()
+, m_weightInit(weightInit)
 , m_w(numVisible, numHidden)
 , m_bv(1, numVisible)
 , m_bh(1, numHidden)
 {
-	weightsInit(0.0, m_params.weightInit);
+	weightsInit(0.0, m_weightInit);
 }
 
 Rbm::Rbm(const Rbm& orig)
@@ -52,11 +53,11 @@ Json::Value Rbm::toJson() const
 	Json::Value rbm;
 	rbm["numVisible"] = m_bv.n_elem;
 	rbm["numHidden"] = m_bh.n_elem;
+	rbm["weightInit"] = m_weightInit;
 	rbm["params"] = m_params.toJson();
 	return rbm;
 }
 
-
 void Rbm::train(const arma::mat& batch, size_t miniBatchSize, size_t numEpochs, IListener* pListener)
 {
 	Status status;
diff --git a/source/Rbm.hpp b/source/Rbm.hpp
index a7b3bc4..7ae07f7 100644
--- a/source/Rbm.hpp
+++ b/source/Rbm.hpp
@@ -26,9 +26,8 @@ public:
 	struct Params
 	{
 		Params()
-		: weightInit(0.01)
+		: learningRate(0.1)
 		, weightDecay(0.0)
-		, learningRate(0.1)
 		, momentum(0.5)
 		, doRaoBlackwell(true)
 		, gibbsDoSampleVisible(false)
@@ -42,7 +41,6 @@ public:
 		{
 			std::cout << "Exporting Rbm::Params" << std::endl;
 			Json::Value params;
-			params["weightInit"] = weightInit;
 			params["weightDecay"] = weightDecay;
 			params["learningRate"] = learningRate;
 			params["momentum"] = momentum;
@@ -57,7 +55,6 @@ public:
 
 		void fromJson(Json::Value params)
 		{
-			weightInit = params["weightInit"].asDouble();
 			weightDecay = params["weightDecay"].asDouble();
 			learningRate = params["learningRate"].asDouble();
 			momentum = params["momentum"].asDouble();
@@ -68,7 +65,6 @@ public:
 			numGibbs = params["numGibbs"].asUInt();
 		}
 		
-		double weightInit;
 		double weightDecay;
 		double learningRate;
 		double momentum;
@@ -112,7 +108,7 @@ public:
 		}
 	};
 
-	Rbm(size_t numVisible, size_t numHidden);
+	Rbm(size_t numVisible, size_t numHidden, double weightInit=0.01);
 	Rbm(const Rbm& orig);
 	virtual ~Rbm();
 
@@ -132,6 +128,7 @@ public:
 	
 private:
 	const Params m_params;
+	double m_weightInit;
 	arma::mat sample(arma::mat const &src);
 	static arma::mat probsLogistic(arma::mat const &src);
 	void uniform(arma::mat &srcDst, double mu=0.0, double stdDev=1.0);
diff --git a/source/RbmLayer.cpp b/source/RbmLayer.cpp
index 8df16de..33acf05 100644
--- a/source/RbmLayer.cpp
+++ b/source/RbmLayer.cpp
@@ -149,7 +149,7 @@ bool RbmLayer::saveWeights(const string &prjname)
 
 Json::Value RbmLayer::toJson() const
 {
-	std::cout << "Exporting RbmLayer " << to_string((int)m_id) << std::endl;
+	std::cout << "Exporting Layer " << to_string((int)m_id) << std::endl;
 	Json::Value layer;
 	layer["name"] = m_name;
 	layer["id"] = (int)m_id;
diff --git a/test.prj b/test.prj
index daddf2b..b4984fb 100644
--- a/test.prj
+++ b/test.prj
@@ -18,9 +18,9 @@
                   "learningRate" : 0.10000000000000001,
                   "momentum" : 0.5,
                   "numGibbs" : 1,
-                  "weightDecay" : 0,
-                  "weightInit" : 0.01
-               }
+                  "weightDecay" : 0
+               },
+               "weightInit" : 0.01
             },
             "weights_file" : "Layer.0.weights.dat"
          }