| 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/* | |