forked from Archives/langchain
You cannot select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
21 lines
1.1 KiB
ReStructuredText
21 lines
1.1 KiB
ReStructuredText
Evaluation
|
|
==============
|
|
|
|
Generative models are notoriously hard to evaluate with traditional metrics. One new way of evaluating them is using language models themselves to do the evaluation. LangChain provides some prompts/chains for assisting in this.
|
|
|
|
The examples here all highlight how to use language models to assist in evaluation of themselves.
|
|
|
|
`Question Answering <./evaluation/question_answering.html>`_: An overview of LLMs aimed at evaluating question answering systems in general.
|
|
|
|
`Data Augmented Question Answering <./evaluation/data_augmented_question_answering.html>`_: An end-to-end example of evaluating a question answering system focused on a specific document (a VectorDBQAChain to be precise). This example highlights how to use LLMs to come up with question/answer examples to evaluate over, and then highlights how to use LLMs to evaluate performance on those generated examples.
|
|
|
|
`Hugging Face Datasets <./evaluation/huggingface_datasets.html>`_: Covers an example of loading and using a dataset from Hugging Face for evaluation.
|
|
|
|
|
|
.. toctree::
|
|
:maxdepth: 1
|
|
:glob:
|
|
:hidden:
|
|
|
|
evaluation/*
|