Update README.md

README.md

@@ -45,7 +45,7 @@ labels = [row[1] for row in csvreader if len(row) > 1]
 model = AutoModelForSequenceClassification.from_pretrained(MODEL)
 model.save_pretrained(MODEL)
 
-text = "Good night 😊"
+text = "Celebrating my promotion 😎"
 text = preprocess(text)
 encoded_input = tokenizer(text, return_tensors='pt')
 output = model(**encoded_input)
@@ -74,8 +74,8 @@ for i in range(scores.shape[0]):
 Output: 
 
 ```
-1) joy 0.9061
-2) optimism 0.0407
-3) sadness 0.0406
-4) anger 0.0126
+1) joy 0.9382
+2) optimism 0.0362
+3) anger 0.0145
+4) sadness 0.0112
 ```