Add description to card metadata (#1)

- Add description to card metadata (1a3c05b2f92af362055ab2b65611a4097fe2cfa5)

README.md

@@ -1,6 +1,6 @@
 ---
 title: ROC AUC
-emoji: 🤗 
+emoji: 🤗
 colorFrom: blue
 colorTo: red
 sdk: gradio
@@ -8,10 +8,24 @@ sdk_version: 3.0.2
 app_file: app.py
 pinned: false
 tags:
-- evaluate
-- metric
+  - evaluate
+  - metric
+description: >-
+  This metric computes the area under the curve (AUC) for the Receiver Operating
+  Characteristic Curve (ROC). The return values represent how well the model
+  used is predicting the correct classes, based on the input data. A score of
+  `0.5` means that the model is predicting exactly at chance, i.e. the model's
+  predictions are correct at the same rate as if the predictions were being
+  decided by the flip of a fair coin or the roll of a fair die. A score above
+  `0.5` indicates that the model is doing better than chance, while a score
+  below `0.5` indicates that the model is doing worse than chance.
+
+
+  This metric has three separate use cases:
+      - binary: The case in which there are only two different label classes, and each example gets only one label. This is the default implementation.
+      - multiclass: The case in which there can be more than two different label classes, but each example still gets only one label.
+      - multilabel: The case in which there can be more than two different label classes, and each example can have more than one label.
 ---
-
 # Metric Card for ROC AUC