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title: ppl | |
tags: | |
- evaluate | |
- metric | |
description: "TODO: add a description here" | |
sdk: gradio | |
sdk_version: 3.19.1 | |
app_file: app.py | |
pinned: false | |
# Metric Card for ppl | |
**_Module Card Instructions:_** _Fill out the following subsections. Feel free to take a look at existing metric cards if you'd like examples._ | |
## Metric Description | |
_Give a brief overview of this metric, including what task(s) it is usually used for, if any._ | |
## How to Use | |
_Give general statement of how to use the metric_ | |
_Provide simplest possible example for using the metric_ | |
### 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 metric outputs and provide an example of what the metric 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 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."_ | |
#### Values from Popular Papers | |
_Give examples, preferrably with links to leaderboards or publications, to papers that have reported this metric, along with the values they have reported._ | |
### 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._ | |