Update README.md

README.md

@@ -4,7 +4,7 @@ emoji: 👁
 colorFrom: red
 colorTo: blue
 sdk: gradio
-sdk_version: 3.9.1
+sdk_version: 5.28.0
 app_file: app.py
 pinned: false
 license: mit
@@ -12,16 +12,16 @@ tags:
 - evaluate
 - metric
 - ranking
-
-description: >- 
-        The Discounted Cumulative Gain is a measure of ranking quality. 
-        It is used to evaluate Information Retrieval Systems under the following 2 assumptions:
-                1. Highly relevant documents/Labels are more useful when appearing earlier in the results
-                2. Documents/Labels are relevant to different degrees
-        It is defined as the Sum over all relevances of the retrieved documents reduced logarithmically proportional to 
-        the position in which they were retrieved.
-        The Normalized DCG (nDCG) divides the resulting value by the best possible value to get a value between 
-        0 and 1 s.t. a perfect retrieval achieves a nDCG of 1.
+description: >-
+  The Discounted Cumulative Gain is a measure of ranking quality.  It is used to
+  evaluate Information Retrieval Systems under the following 2 assumptions:
+          1. Highly relevant documents/Labels are more useful when appearing earlier in the results
+          2. Documents/Labels are relevant to different degrees
+  It is defined as the Sum over all relevances of the retrieved documents
+  reduced logarithmically proportional to  the position in which they were
+  retrieved. The Normalized DCG (nDCG) divides the resulting value by the best
+  possible value to get a value between  0 and 1 s.t. a perfect retrieval
+  achieves a nDCG of 1.
 ---
 
 # Metric Card for nDCG