Update Space (evaluate main: e179b5b8)

README.md

@@ -1,6 +1,6 @@
 ---
 title: SARI
-emoji: 🤗
+emoji: 🤗 
 colorFrom: blue
 colorTo: red
 sdk: gradio
@@ -8,45 +8,10 @@ sdk_version: 3.0.2
 app_file: app.py
 pinned: false
 tags:
-  - 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
+- evaluate
+- metric
 ---
+
 # Metric Card for SARI