updated description

app.py

@@ -12,7 +12,7 @@ stemmer = WordNetLemmatizer()
 from keras.preprocessing.text import Tokenizer
 from keras import backend as K
 
-#Завантажуємо наші моделі
+#defining some variables and test parametrics
 
 def recall(y_true, y_pred):
     true_positives = K.sum(K.round(K.clip(y_true * y_pred, 0, 1)))
@@ -56,6 +56,6 @@ def get_sentiment(text):
     x = model.predict(text).tolist()[0][0]
     return x 
 
-interface = gr.Interface(fn = get_sentiment, inputs = 'text', outputs = 'text', title = 'Kotsko Kyrylo IPS-42 Sentiment140', description = 'Kotsko Kyrylo IPS-42 Sentiment140')
+interface = gr.Interface(fn = get_sentiment, inputs = 'text', outputs = 'text', title = 'Sentiment Analysis', description = 'uses a custom designed model for sentiment analysis.')
 
 interface.launch(share=False)