Update README.md

README.md

@@ -10,7 +10,7 @@ This model is obtained by finetuning a Pre-Trained RoBERTa using a dataset encom
 Using this model, we can classify malicious prompts that can lead towards creation of phishing websites and phishing emails. -->
 
 Our model, "ScamLLM" is designed to identify malicious prompts that can be used to generate phishing websites and emails using popular commercial LLMs like ChatGPT, Bard and Claude.
-This model is obtained by finetuning a Pre-Trained RoBERTa using a dataset encompassing multiple sets of malicious prompts, as detailed in our corresponding arXiv paper
+This model is obtained by finetuning a Pre-Trained RoBERTa using a dataset encompassing multiple sets of malicious prompts. 
 
 <!--- **Paper:** https://arxiv.org/abs/2310.19181 -->
 
@@ -41,7 +41,7 @@ print(model_outputs[0])
 
 ### Results
 
-Achieved an accuracy of 96% with an F1-score of 0.96, on test sets distribution, explained in the paper. 
+Achieved an accuracy of 94% with an F1-score of 0.94, on test sets.  
 
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