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| title: SEScore | |
| datasets: | |
| - | |
| tags: | |
| - evaluate | |
| - metric | |
| description: "SEScore: a text generation evaluation metric" | |
| sdk: gradio | |
| sdk_version: 3.0.2 | |
| app_file: app.py | |
| pinned: false | |
| # Metric Card for SEScore | |
|  | |
| ## Metric Description | |
| *SEScore is an unsupervised learned evaluation metric trained on synthesized dataset* | |
| ## How to Use | |
| *Provide simplest possible example for using the metric* | |
| ### Inputs | |
| *SEScore takes input of predictions (a list of candidate translations) and references (a list of reference translations).* | |
| ### Output Values | |
| *Output value is between 0 to -25* | |
| #### Values from Popular Papers | |
| ### 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.* | |
| ## Limitations and Bias | |
| *Note any known limitations or biases that the metric has, with links and references if possible.* | |
| ## Citation | |
| *Cite the source where this metric was introduced.* | |
| ## Further References | |
| *Add any useful further references.* | |