README.md

---
title: ccl_win
datasets:
- arxiv
- pubmed  
tags:
- local-coherence
- evaluate
- measurement
description: "local coherence using window classifier"
sdk: gradio
sdk_version: 3.19.1
app_file: app.py
pinned: false
---

# Measurement Card for ccl_win

***Module Card Instructions:*** *Fill out the following subsections. Feel free to take a look at existing measurement cards if you'd like examples.*

## Measurement Description
local coherence using classf in window of 3 sents

## How to Use
*Give general statement of how to use the measurement*

*Provide simplest possible example for using the measurement*

### Inputs
*List all input arguments in the format below*
- **input_field** *(type): Definition of input, with explanation if necessary. State any default value(s).*

### Output Values

*Explain what this measurement outputs and provide an example of what the measurement 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 measurement's output can take, as well as what in that range is considered good. For example: "This measurement can take on any value between 0 and 100, inclusive. Higher scores are better."*

#### Values from Popular Papers
*Give examples, preferrably with links to leaderboards or publications, to papers that have reported this measurement, along with the values they have reported.*

### Examples
*Give code examples of the measurement being used. Try to include examples that clear up any potential ambiguity left from the measurement 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 measurement has, with links and references if possible.*

## Citation
*Cite the source where this measurement was introduced.*

## Further References
*Add any useful further references.*