edit photos

README.md

@@ -12,32 +12,26 @@ app_file: app.py
 pinned: false
 ---
 
-<img src="img/logo_sescore.png" alt="Alt text" title="SEScore logo">
-
 # Metric Card for SEScore
+<img src="img/logo_sescore.png" alt="Alt text" title="SEScore logo">
 
-***Module Card Instructions:*** *Fill out the following subsections. Feel free to take a look at existing metric cards if you'd like examples.*
 
 ## Metric Description
-*Give a brief overview of this metric, including what task(s) it is usually used for, if any.*
+*SEScore is an unsupervised learned evaluation metric trained on synthesized dataset*
 
 ## How to Use
-*Give general statement of how to use the metric*
 
 *Provide simplest possible example for using the metric*
 
 ### Inputs
-*List all input arguments in the format below*
-- **input_field** *(type): Definition of input, with explanation if necessary. State any default value(s).*
+*SEScore takes input of predictions (a list of candidate translations) and references (a list of reference translations).*
 
 ### Output Values
 
-*Explain what this metric outputs and provide an example of what the metric output looks like. Modules should return a dictionary with one or multiple key-value pairs, e.g. {"bleu" : 6.02}*
-
-*State the range of possible values that the metric's output can take, as well as what in that range is considered good. For example: "This metric can take on any value between 0 and 100, inclusive. Higher scores are better."*
+*Output value is between 0 to -25*
 
 #### Values from Popular Papers
-*Give examples, preferrably with links to leaderboards or publications, to papers that have reported this metric, along with the values they have reported.*
+
 
 ### Examples
 *Give code examples of the metric being used. Try to include examples that clear up any potential ambiguity left from the metric description above. If possible, provide a range of examples that show both typical and atypical results, as well as examples where a variety of input parameters are passed.*