Add description to card metadata

BLEURT a learnt evaluation metric for Natural Language Generation. It is built using multiple phases of transfer learning starting from a pretrained BERT model (Devlin et al. 2018)
and then employing another pre-training phrase using synthetic data. Finally it is trained on WMT human annotations. You may run BLEURT out-of-the-box or fine-tune
it for your specific application (the latter is expected to perform better).

See the project's README at https://github.com/google-research/bleurt#readme for more information.

README.md

@@ -1,6 +1,6 @@
 ---
 title: BLEURT
-emoji: 🤗 
+emoji: 🤗
 colorFrom: blue
 colorTo: red
 sdk: gradio
@@ -8,10 +8,23 @@ sdk_version: 3.0.2
 app_file: app.py
 pinned: false
 tags:
-- evaluate
-- metric
----
+  - evaluate
+  - metric
+description: >-
+  BLEURT a learnt evaluation metric for Natural Language Generation. It is built
+  using multiple phases of transfer learning starting from a pretrained BERT
+  model (Devlin et al. 2018)
+
+  and then employing another pre-training phrase using synthetic data. Finally
+  it is trained on WMT human annotations. You may run BLEURT out-of-the-box or
+  fine-tune
+
+  it for your specific application (the latter is expected to perform better).
 
+
+  See the project's README at https://github.com/google-research/bleurt#readme
+  for more information.
+---
 # Metric Card for BLEURT