diff --git a/.idea/workspace.xml b/.idea/workspace.xml
index 199c7fb..9c87a0a 100644
--- a/.idea/workspace.xml
+++ b/.idea/workspace.xml
@@ -47,7 +47,7 @@
         <counts>
           <entry key="Dockerfile" value="81" />
           <entry key="md" value="104" />
-          <entry key="py" value="2445" />
+          <entry key="py" value="2449" />
           <entry key="sh" value="5" />
         </counts>
       </usages-collector>
@@ -56,7 +56,7 @@
           <entry key="Bash" value="5" />
           <entry key="Dockerfile" value="81" />
           <entry key="Markdown" value="104" />
-          <entry key="Python" value="2445" />
+          <entry key="Python" value="2449" />
         </counts>
       </usages-collector>
     </session>
@@ -91,8 +91,8 @@
       <file pinned="false" current-in-tab="true">
         <entry file="file://$PROJECT_DIR$/train.py">
           <provider selected="true" editor-type-id="text-editor">
-            <state relative-caret-position="185">
-              <caret line="73" column="16" lean-forward="true" selection-start-line="73" selection-start-column="16" selection-end-line="73" selection-end-column="16" />
+            <state relative-caret-position="257">
+              <caret line="79" column="38" selection-start-line="79" selection-start-column="28" selection-end-line="79" selection-end-column="38" />
               <folding>
                 <element signature="e#0#28#0" expanded="true" />
               </folding>
@@ -223,7 +223,7 @@
   <component name="PropertiesComponent">
     <property name="WebServerToolWindowFactoryState" value="false" />
     <property name="aspect.path.notification.shown" value="true" />
-    <property name="com.android.tools.idea.instantapp.provision.ProvisionBeforeRunTaskProvider.myTimeStamp" value="1588382857916" />
+    <property name="com.android.tools.idea.instantapp.provision.ProvisionBeforeRunTaskProvider.myTimeStamp" value="1588383124284" />
     <property name="go.gopath.indexing.explicitly.defined" value="true" />
     <property name="nodejs_interpreter_path.stuck_in_default_project" value="undefined stuck path" />
     <property name="nodejs_npm_path_reset_for_default_project" value="true" />
@@ -264,12 +264,12 @@
       <option name="presentableId" value="Default" />
       <updated>1588152877746</updated>
       <workItem from="1588152880522" duration="16973000" />
-      <workItem from="1588319878551" duration="18765000" />
+      <workItem from="1588319878551" duration="18998000" />
     </task>
     <servers />
   </component>
   <component name="TimeTrackingManager">
-    <option name="totallyTimeSpent" value="35738000" />
+    <option name="totallyTimeSpent" value="35971000" />
   </component>
   <component name="ToolWindowManager">
     <frame x="0" y="0" width="1280" height="800" extended-state="0" />
@@ -395,8 +395,8 @@
     </entry>
     <entry file="file://$PROJECT_DIR$/train.py">
       <provider selected="true" editor-type-id="text-editor">
-        <state relative-caret-position="185">
-          <caret line="73" column="16" lean-forward="true" selection-start-line="73" selection-start-column="16" selection-end-line="73" selection-end-column="16" />
+        <state relative-caret-position="257">
+          <caret line="79" column="38" selection-start-line="79" selection-start-column="28" selection-end-line="79" selection-end-column="38" />
           <folding>
             <element signature="e#0#28#0" expanded="true" />
           </folding>
diff --git a/train.py b/train.py
index 7a64ced..e50861a 100644
--- a/train.py
+++ b/train.py
@@ -81,6 +81,8 @@ def forecast_lstm(model, batch_size, X):
 	return yhat[0, 0]
 
 
+batch_size = 12
+
 # load dataset
 series = read_csv('data.csv', header=0, index_col=0, squeeze=True)
 
@@ -99,17 +101,17 @@ train, test = supervised_values[0:-12], supervised_values[-12:]
 scaler, train_scaled, test_scaled = scale(train, test)
 
 # fit the model
-lstm_model = fit_lstm(train_scaled, 32, 30, 4)
+lstm_model = fit_lstm(train_scaled, batch_size, 30, 4)
 # forecast the entire training dataset to build up state for forecasting
 train_reshaped = train_scaled[:, 0].reshape(len(train_scaled), 1, 1)
-lstm_model.predict(train_reshaped, batch_size=32)
+lstm_model.predict(train_reshaped, batch_size=batch_size)
 
 # walk-forward validation on the test data
 predictions = list()
 for j in range(len(test_scaled)):
 	# make one-step forecast
 	X, y = test_scaled[j, 0:-1], test_scaled[j, -1]
-	yhat = forecast_lstm(lstm_model, 32, X)
+	yhat = forecast_lstm(lstm_model, batch_size, X)
 	# invert scaling
 	yhat = invert_scale(scaler, X, yhat)
 	# invert differencing