Update README.md

README.md

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 # Twitter-roBERTa-base for Sentiment Analysis
 
-This is a roBERTa-base model trained on ~58M tweets and finetuned for the Sentiment Analysis task at Semeval 2018. 
-For full description: [_TweetEval_ benchmark (Findings of EMNLP 2020)](https://arxiv.org/pdf/2010.12421.pdf). 
-To evaluate this and other models on Twitter-specific data, please refer to the [Tweeteval official repository](https://github.com/cardiffnlp/tweeteval).
+This is a roBERTa-base model trained on ~58M tweets and finetuned for sentiment analysis with the TweetEval benchmark.
+
+- Paper: [_TweetEval_ benchmark (Findings of EMNLP 2020)](https://arxiv.org/pdf/2010.12421.pdf). 
+- Git Repo: [Tweeteval official repository](https://github.com/cardiffnlp/tweeteval).
 
 ## Example of classification
 
@@ -18,6 +19,8 @@ import urllib.request
 # Preprocess text (username and link placeholders)
 def preprocess(text):
     new_text = []
+ 
+ 
     for t in text.split(" "):
         t = '@user' if t.startswith('@') and len(t) > 1 else t
         t = 'http' if t.startswith('http') else t