Update README.md

README.md

@@ -46,7 +46,7 @@ tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
 model = AutoModelForSequenceClassification.from_pretrained(MODEL_PATH)
 
 text = "We deden een man een nacht in een vat met cola en nu is hij dood"
-tokenized_text = tokenizer([preprocess_data(text)], padding=True, truncation=True, max_length=512, return_tensors="pt")
+tokenized_text = tokenizer([preprocess_data(text)], padding=True, truncation=True, max_length=256, return_tensors="pt")
 output = model(**tokenized_text)
 probs = output.logits.softmax(dim=-1).tolist()[0]
 confidence = max(probs)
@@ -58,7 +58,7 @@ results = {"is_sarcastic": prediction, "confidence": confidence}
 Output: 
 
 ```
-{'is_sarcastic': 1, 'confidence': 0.9999982118606567}
+{'is_sarcastic': 1, 'confidence': 0.8915400505065918}
 ```
 
 ## Performance