Add description to card metadata

README.md

@@ -1,6 +1,6 @@
 ---
 title: SARI
-emoji: 🤗 
+emoji: 🤗
 colorFrom: blue
 colorTo: red
 sdk: gradio
@@ -8,10 +8,45 @@ sdk_version: 3.0.2
 app_file: app.py
 pinned: false
 tags:
-- evaluate
-- metric
----
+  - evaluate
+  - metric
+description: >-
+  SARI is a metric used for evaluating automatic text simplification systems.
+
+  The metric compares the predicted simplified sentences against the reference
+
+  and the source sentences. It explicitly measures the goodness of words that
+  are
+
+  added, deleted and kept by the system.
+
+  Sari = (F1_add + F1_keep + P_del) / 3
+
+  where
+
+  F1_add: n-gram F1 score for add operation
 
+  F1_keep: n-gram F1 score for keep operation
+
+  P_del: n-gram precision score for delete operation
+
+  n = 4, as in the original paper.
+
+
+  This implementation is adapted from Tensorflow's tensor2tensor implementation
+  [3].
+
+  It has two differences with the original GitHub [1] implementation:
+    (1) Defines 0/0=1 instead of 0 to give higher scores for predictions that match
+        a target exactly.
+    (2) Fixes an alleged bug [2] in the keep score computation.
+  [1] https://github.com/cocoxu/simplification/blob/master/SARI.py
+      (commit 0210f15)
+  [2] https://github.com/cocoxu/simplification/issues/6
+
+  [3]
+  https://github.com/tensorflow/tensor2tensor/blob/master/tensor2tensor/utils/sari_hook.py
+---
 # Metric Card for SARI