Update README.md

README.md

@@ -149,15 +149,6 @@ The model was evaluated on the test split of the MIT Restaurant Search NER datas
 
 These metrics were calculated using the seqeval library, which evaluates NER performance at the entity level rather than token level.
 
-### Results
-
-The model achieves [add summary of performance] on the test set. It performs particularly well on [mention any entity types with notably good performance] and less reliably on [mention challenging entity types].
-
-## Environmental Impact
-
-- **Hardware Type:** [CPU/GPU model used]
-- **Hours used:** [Approximate training time]
-- **Cloud Provider:** [If applicable]
 
 ## Technical Specifications
 
@@ -173,4 +164,4 @@ The model uses DistilBERT with a token classification head. DistilBERT is a smal
 
 ## Model Card Contact
 
-[Your contact information or GitHub username]
+https://niruthiha.github.io/