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Update readme
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README.md
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---
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title: action_generation
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datasets:
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tags:
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- evaluate
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- metric
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*Give general statement of how to use the metric*
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*Provide simplest possible example for using the metric*
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### Inputs
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*List all input arguments in the format below*
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---
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title: action_generation
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datasets:
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tags:
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- evaluate
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- metric
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*Give general statement of how to use the metric*
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*Provide simplest possible example for using the metric*
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```python
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import evaluate
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valid_labels = [
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"/開箱",
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"/教學",
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"/表達",
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"/分享/外部資訊",
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"/分享/個人資訊",
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"/推薦/產品",
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"/推薦/服務",
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"/推薦/其他",
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""
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]
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predictions = [
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["/開箱/xxx", "/教學/yyy", "/表達/zzz"],
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["/分享/外部資訊/aaa", "/教學/yyy", "/表達/zzz", "/分享/個人資訊/bbb"]
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]
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references = [
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["/開箱/xxx", "/教學/yyy", "/表達/zzz"],
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["/推薦/產品/bbb", "/教學/yyy", "/表達/zzz"]
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]
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metric = evaluate.load("DarrenChensformer/action_generation")
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result = metric.compute(predictions=predictions, references=references, valid_labels=valid_labels, detailed_scores=True)
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print(result)
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```
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### Inputs
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*List all input arguments in the format below*
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