diff --git a/neural_network.py b/neural_network.py
index ec58259..99f3ac5 100644
--- a/neural_network.py
+++ b/neural_network.py
@@ -19,17 +19,14 @@ y = NormalizeData(y)
 
 
 model = keras.Sequential([
-    keras.layers.Dense(512,input_dim = X.shape[1],kernel_initializer='normal', activation='relu'),
-    keras.layers.Dense(512,kernel_initializer='normal', activation='relu'),
-    keras.layers.Dense(256,kernel_initializer='normal', activation='relu'),
-    keras.layers.Dense(256,kernel_initializer='normal', activation='relu'),
-    keras.layers.Dense(128,kernel_initializer='normal', activation='relu'),
-    keras.layers.Dense(1,kernel_initializer='normal', activation='linear'),
+    keras.layers.Dense(32,input_dim = X.shape[1],kernel_initializer='normal', activation='relu'),
+    keras.layers.Dense(64,kernel_initializer='normal', activation='relu'),
+    keras.layers.Dense(1,kernel_initializer='normal', activation='relu'),
 ])
 
 model.compile(loss='mean_absolute_error', optimizer='adam', metrics=['mean_absolute_error'])
 
-model.fit(X, y, epochs=30, validation_split = 0.3)
+model.fit(X, y, epochs=15, validation_split = 0.3)
 
 data = pd.read_csv("data_test", sep=',', error_bad_lines=False).dropna()
 X_test = data.loc[:,data.columns == "2805317"].astype(int)