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Add metric description

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  # Metric Card for action_generation
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- ***Module Card Instructions:*** *Fill out the following subsections. Feel free to take a look at existing metric cards if you'd like examples.*
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-
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  ## Metric Description
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- *Give a brief overview of this metric, including what task(s) it is usually used for, if any.*
 
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  ## How to Use
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- *Give general statement of how to use the metric*
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-
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- *Provide simplest possible example for using the metric*
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-
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  ```python
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  import evaluate
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  valid_labels = [
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  *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."*
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- #### Values from Popular Papers
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- *Give examples, preferrably with links to leaderboards or publications, to papers that have reported this metric, along with the values they have reported.*
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  ### Examples
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  *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.*
 
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  # Metric Card for action_generation
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  ## Metric Description
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+ Evaluate the result of action generation task.
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+ Consider the output format `/class/phrase`. Compute the scores for both `/class` and `phrase` separately, and then perform a weighted sum of these scores.
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  ## How to Use
 
 
 
 
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  ```python
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  import evaluate
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  valid_labels = [
 
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  *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."*
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  ### Examples
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  *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.*