updated basic info

src/about.py

@@ -7,6 +7,7 @@ class Task:
     benchmark: str
     metric: str
     col_name: str
+    
 
 
 # Select your tasks here
@@ -28,16 +29,30 @@ NUM_FEWSHOT = 0  # Change with your few shot
 
 
 # Your leaderboard name
-TITLE = """<h1 align="center" id="space-title">BioMed NER Leaderboard</h1>"""
+TITLE = """<h1 align="center" id="space-title">MEDICS NER Leaderboard</h1>"""
 
 # What does your leaderboard evaluate?
 INTRODUCTION_TEXT = """
-Intro text
 """
 
 # Which evaluations are you running? how can people reproduce what you have?
 LLM_BENCHMARKS_TEXT = f"""
-## How it works
+## About
+Named Entity Recogintion is a significant task for information extraction. However, we do not have a open leaderboard to rank the NER capabilities of models in the Bio-Medical domain.
+
+MEDICS NER leaderboard aims to solve this by quantifying NER performance on open-source datasets. 
+To keep the evaluation widely relevant the entity types in the dataset are mapped to broader M2 types. More information on this mapping can be found here - M2-DATASETS-ARTICLE-LINK
+
+### Tasks
+📈 We evaluate models on X key datasets, encompassing Y entity types
+- NCBI - INFO
+- CHIA
+- BIORED
+- BC5CD
+
+### Evaluation Metrics
+
+
 
 ## Reproducibility
 To reproduce our results, here is the commands you can run: