Update app.py

app.py

@@ -21,7 +21,7 @@ def predict(model, txt):
     pipe_roberta = pipeline("sentiment-analysis", model="cardiffnlp/twitter-roberta-base-sentiment-latest", tokenizer="cardiffnlp/twitter-roberta-base-sentiment-latest")
 
     #pipeline for finbert
-    tokenizer = BertTokenizer.from_pretrained('yiyanghkust/finbert-tone')
+    tokenizer_f = BertTokenizer.from_pretrained('yiyanghkust/finbert-tone')
     pipe_finbert = pipeline("sentiment-analysis", model="yiyanghkust/finbert-tone", tokenizer=tokenizer_f)
     pipe_bart = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")
     res = pipe_bart(txt, labels)['scores']
@@ -52,7 +52,7 @@ def predict(model, txt):
         score = fin_res['score']
         fin_res = []
         for sc in res:
-            fin_res.append(sc + (0.7421 * (label + 0.05) * random.random() * sc) )
+            fin_res.append(sc + (0.4429 * (label + 0.05) * random.random() * sc) )
 
         return fin_res