Add description to card metadata (#1)

- Add description to card metadata (7225d348814f2cd6060148dac482fdd5f7b834b0)

README.md

@@ -1,6 +1,6 @@
 ---
 title: BLEU
-emoji: 🤗 
+emoji: 🤗
 colorFrom: blue
 colorTo: red
 sdk: gradio
@@ -8,10 +8,44 @@ sdk_version: 3.0.2
 app_file: app.py
 pinned: false
 tags:
-- evaluate
-- metric
----
+  - evaluate
+  - metric
+description: >-
+  BLEU (bilingual evaluation understudy) is an algorithm for evaluating the
+  quality of text which has been machine-translated from one natural language to
+  another.
+
+  Quality is considered to be the correspondence between a machine's output and
+  that of a human: "the closer a machine translation is to a professional human
+  translation,
+
+  the better it is" – this is the central idea behind BLEU. BLEU was one of the
+  first metrics to claim a high correlation with human judgements of quality,
+  and
+
+  remains one of the most popular automated and inexpensive metrics.
+
+
+  Scores are calculated for individual translated segments—generally
+  sentences—by comparing them with a set of good quality reference translations.
+
+  Those scores are then averaged over the whole corpus to reach an estimate of
+  the translation's overall quality. Intelligibility or grammatical correctness
 
+  are not taken into account[citation needed].
+
+
+  BLEU's output is always a number between 0 and 1. This value indicates how
+  similar the candidate text is to the reference texts, with values closer to 1
+
+  representing more similar texts. Few human translations will attain a score of
+  1, since this would indicate that the candidate is identical to one of the
+
+  reference translations. For this reason, it is not necessary to attain a score
+  of 1. Because there are more opportunities to match, adding additional
+
+  reference translations will increase the BLEU score.
+---
 # Metric Card for BLEU