Add round

app.py

@@ -368,7 +368,7 @@ def load_model(tweet):
 def greet(tweet):
     print("start")
     prediction = load_model(tweet)
-    prediction_value = prediction.item()
+    prediction_value = round(prediction.item(),2)
     # features_list = extract_features(tweet)
     # print(personality_detection(tweet))
     # print(str(features_list["Average_Word_Length"]))
@@ -376,9 +376,9 @@ def greet(tweet):
     predicted_class = torch.round(prediction).item()
     print("end")
     if (predicted_class==0.0):
-        label = "Hate"
-    else:
         label = "Non Hate"
+    else:
+        label = "Hate"
     
 
     return label,str(prediction_value)+"%",str(1-prediction_value)+"%"