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Add description to card metadata (#1)

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- Add description to card metadata (82fd13c2f2d3c6013f33cd94d0580f62802dd3da)

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  1. README.md +39 -4
README.md CHANGED
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  ---
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  title: SARI
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- emoji: 🤗
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  colorFrom: blue
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  colorTo: red
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  sdk: gradio
@@ -8,10 +8,45 @@ sdk_version: 3.0.2
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  app_file: app.py
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  pinned: false
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  tags:
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- - evaluate
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- - metric
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  # Metric Card for SARI
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  ---
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  title: SARI
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+ emoji: 🤗
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  colorFrom: blue
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  colorTo: red
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  sdk: gradio
 
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  app_file: app.py
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  pinned: false
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  tags:
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+ - evaluate
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+ - metric
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+ description: >-
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+ SARI is a metric used for evaluating automatic text simplification systems.
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+
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+ The metric compares the predicted simplified sentences against the reference
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+
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+ and the source sentences. It explicitly measures the goodness of words that
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+ are
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+
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+ added, deleted and kept by the system.
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+
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+ Sari = (F1_add + F1_keep + P_del) / 3
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+
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+ where
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+
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+ F1_add: n-gram F1 score for add operation
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+ F1_keep: n-gram F1 score for keep operation
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+
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+ P_del: n-gram precision score for delete operation
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+
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+ n = 4, as in the original paper.
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+
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+
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+ This implementation is adapted from Tensorflow's tensor2tensor implementation
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+ [3].
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+
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+ It has two differences with the original GitHub [1] implementation:
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+ (1) Defines 0/0=1 instead of 0 to give higher scores for predictions that match
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+ a target exactly.
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+ (2) Fixes an alleged bug [2] in the keep score computation.
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+ [1] https://github.com/cocoxu/simplification/blob/master/SARI.py
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+ (commit 0210f15)
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+ [2] https://github.com/cocoxu/simplification/issues/6
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+
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+ [3]
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+ https://github.com/tensorflow/tensor2tensor/blob/master/tensor2tensor/utils/sari_hook.py
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+ ---
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  # Metric Card for SARI
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