README.md

---
title: SEScore
datasets:
- null
tags:
- evaluate
- metric
description: 'SEScore: a text generation evaluation metric'
sdk: gradio
sdk_version: 3.0.2
app_file: app.py
pinned: false
duplicated_from: xu1998hz/sescore
---

# Metric Card for SEScore
![alt text](https://huggingface.co/spaces/xu1998hz/sescore/blob/main/img/logo_sescore.png)

## 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.*