Update README.md

README.md

@@ -29,14 +29,14 @@ You can use the model simply by running the following:
 >>> from transformers import pipeline
 >>> offensive_text_pipeline = pipeline(model="xlm-roberta-base-offensive-text-detection-da")
 >>> offensive_text_pipeline("Din store idiot")
-[{'label': 'offensive', 'score': 0.9874388575553894}]
+[{'label': 'Offensive', 'score': 0.9997463822364807}]
 ```
 
 Processing multiple documents at the same time can be done as follows:
 
 ```python
 >>> offensive_text_pipeline(["Din store idiot", "ej hvor godt :)"])
-[{'label': 'offensive', 'score': 0.9874388575553894}, {'label': 'not offensive', 'score': 0.999760091304779}]
+[{'label': 'Offensive', 'score': 0.9997463822364807}, {'label': 'Not offensive', 'score': 0.9996451139450073}]
 ```
 
 ## Training procedure