{"id":4123,"date":"2026-03-20T15:35:02","date_gmt":"2026-03-20T15:35:02","guid":{"rendered":"https:\/\/proleed.academy\/blog\/?p=4123"},"modified":"2026-03-26T07:08:10","modified_gmt":"2026-03-26T07:08:10","slug":"how-to-evaluate-rag-systems-key-metrics-every-ai-engineer-should-know","status":"publish","type":"post","link":"https:\/\/proleed.academy\/blog\/how-to-evaluate-rag-systems-key-metrics-every-ai-engineer-should-know\/","title":{"rendered":"How to Evaluate RAG Systems: Key Metrics Every AI Engineer Should Know"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"4123\" class=\"elementor elementor-4123\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-14b7d63 elementor-section-full_width elementor-section-height-default elementor-section-height-default\" data-id=\"14b7d63\" data-element_type=\"section\" data-e-type=\"section\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-33 elementor-top-column elementor-element elementor-element-bc4fb49\" data-id=\"bc4fb49\" data-element_type=\"column\" data-e-type=\"column\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-a549fff elementor-widget elementor-widget-heading\" data-id=\"a549fff\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Table of contents<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f90f066 elementor-icon-list--layout-traditional elementor-list-item-link-full_width elementor-widget elementor-widget-icon-list\" data-id=\"f90f066\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"icon-list.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<ul class=\"elementor-icon-list-items\">\n\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/proleed.academy\/blog\/how-to-evaluate-rag-systems-key-metrics-every-ai-engineer-should-know\/#topic1\">\n\n\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"fas fa-chevron-right\"><\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Introduction<\/span>\n\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/proleed.academy\/blog\/how-to-evaluate-rag-systems-key-metrics-every-ai-engineer-should-know\/#topic2\">\n\n\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"fas fa-chevron-right\"><\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">What Is RAG Evaluation? Understanding the RAG Evaluation Problem<\/span>\n\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/proleed.academy\/blog\/how-to-evaluate-rag-systems-key-metrics-every-ai-engineer-should-know\/#topic3\">\n\n\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"fas fa-chevron-right\"><\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">The Three Layers of RAG Evaluation<\/span>\n\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/proleed.academy\/blog\/how-to-evaluate-rag-systems-key-metrics-every-ai-engineer-should-know\/#topic4\">\n\n\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"fas fa-chevron-right\"><\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Important Like How to Measure Retrieval Metrics<\/span>\n\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/proleed.academy\/blog\/how-to-evaluate-rag-systems-key-metrics-every-ai-engineer-should-know\/#topic5\">\n\n\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"fas fa-chevron-right\"><\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Generation Metrics That Actually Matter<\/span>\n\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/proleed.academy\/blog\/how-to-evaluate-rag-systems-key-metrics-every-ai-engineer-should-know\/#topic6\">\n\n\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"fas fa-chevron-right\"><\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">End-to-End RAG System Metrics<\/span>\n\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/proleed.academy\/blog\/how-to-evaluate-rag-systems-key-metrics-every-ai-engineer-should-know\/#topic7\">\n\n\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"fas fa-chevron-right\"><\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">LLM-Based Evaluation Approaches<\/span>\n\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/proleed.academy\/blog\/how-to-evaluate-rag-systems-key-metrics-every-ai-engineer-should-know\/#topic8\">\n\n\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"fas fa-chevron-right\"><\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Common Mistakes When Evaluating RAG Systems<\/span>\n\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/proleed.academy\/blog\/how-to-evaluate-rag-systems-key-metrics-every-ai-engineer-should-know\/#topic9\">\n\n\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"fas fa-chevron-right\"><\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Best Practices for Reliable RAG Evaluation<\/span>\n\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/proleed.academy\/blog\/how-to-evaluate-rag-systems-key-metrics-every-ai-engineer-should-know\/#topic10\">\n\n\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"fas fa-chevron-right\"><\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Conclusion<\/span>\n\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t\t\t<li class=\"elementor-icon-list-item\">\n\t\t\t\t\t\t\t\t\t\t\t<a href=\"https:\/\/proleed.academy\/blog\/how-to-evaluate-rag-systems-key-metrics-every-ai-engineer-should-know\/#topic11\">\n\n\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-icon\">\n\t\t\t\t\t\t\t<i aria-hidden=\"true\" class=\"fas fa-chevron-right\"><\/i>\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-icon-list-text\">Frequently Asked Questions <\/span>\n\t\t\t\t\t\t\t\t\t\t\t<\/a>\n\t\t\t\t\t\t\t\t\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-66 elementor-top-column elementor-element elementor-element-5f3dc80\" data-id=\"5f3dc80\" data-element_type=\"column\" data-e-type=\"column\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;}\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-6872c5f elementor-widget elementor-widget-heading\" data-id=\"6872c5f\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h1 class=\"elementor-heading-title elementor-size-default\">How to Evaluate RAG Systems: Key Metrics Every AI Engineer Should Know<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-edec6a1 elementor-widget elementor-widget-menu-anchor\" data-id=\"edec6a1\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"menu-anchor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-menu-anchor\" id=\"topic1\"><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2ea264b elementor-widget elementor-widget-heading\" data-id=\"2ea264b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Introduction<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3c0201c elementor-widget elementor-widget-text-editor\" data-id=\"3c0201c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">RAG (Retrieval-Augmented Generation) has been increasingly adopted in AI because it allows for a combination of information retrieval along with large language models to create answers that are based on outside sources of knowledge.<\/span><\/p><p><span style=\"font-weight: 400;\">However, evaluating RAG systems is more complex than evaluating traditional machine learning models because errors can occur in both the retrieval and generation stages, making it difficult to determine which component (retriever, generator) is responsible for failures.<\/span><\/p><p><span style=\"font-weight: 400;\">Understanding how best to evaluate these types of systems is critical for AI engineers developing systems that function reliably. As a result, many applied learning opportunities, such as structured <\/span><em><span style=\"text-decoration: underline;\"><a href=\"https:\/\/proleed.academy\/artificial-intelligence-ai-training-course.php\"><b>AI training programs<\/b><\/a><\/span><\/em><span style=\"font-weight: 400;\">, actively incorporate system evaluation activities into the overall development of AI models. This article discusses the essential metrics that are important to consider when evaluating Retrieval-Augmented Generation (RAG) systems.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4625426 elementor-widget elementor-widget-spacer\" data-id=\"4625426\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6032684 elementor-widget elementor-widget-menu-anchor\" data-id=\"6032684\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"menu-anchor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-menu-anchor\" id=\"topic2\"><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4e00149 elementor-widget elementor-widget-heading\" data-id=\"4e00149\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">What Is RAG Evaluation? Understanding the RAG Evaluation Problem<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-bcec3e0 elementor-widget elementor-widget-text-editor\" data-id=\"bcec3e0\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">RAG evaluation measures the effectiveness of retrieval, generation quality, and overall system performance in retrieval-augmented generation pipelines.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2458581 elementor-widget elementor-widget-image\" data-id=\"2458581\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img fetchpriority=\"high\" decoding=\"async\" width=\"1408\" height=\"768\" src=\"https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/understanding-the-rag-evaluation-problem.webp\" class=\"attachment-full size-full wp-image-4204\" alt=\"Understanding the RAG Evaluation Problem\" srcset=\"https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/understanding-the-rag-evaluation-problem.webp 1408w, https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/understanding-the-rag-evaluation-problem-300x164.webp 300w, https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/understanding-the-rag-evaluation-problem-1024x559.webp 1024w, https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/understanding-the-rag-evaluation-problem-768x419.webp 768w\" sizes=\"(max-width: 1408px) 100vw, 1408px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5655bd7 elementor-widget elementor-widget-text-editor\" data-id=\"5655bd7\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">RAG architecture is composed of two major components:\u00a0<\/span><\/p><ol><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">A retrieval system that finds suitable documents or other knowledge sources.<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">A generation system that produces the final answer from the retrieved documents or knowledge.<\/span><\/li><\/ol><p><span style=\"font-weight: 400;\">These components make it more complicated to evaluate RAG models than other models. Failures can occur at multiple steps in the pipeline:<\/span><\/p><ul><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The retrieval system may return irrelevant documents<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The model could misinterpret the retrieved context.<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">The LLM could hallucinate information that is contrary to what is stated.<\/span><\/li><\/ul><p><span style=\"font-weight: 400;\">Because of this complexity in evaluating RAG systems, it is difficult to determine accountability for error cases when only using the output of the generation system. An output could show to be wrong because the retrieval failed and not necessarily because of the generation quality.<\/span><\/p><p><span style=\"font-weight: 400;\">There are many online open-source frameworks (such as LangChain and LlamaIndex) that allow developers to link retrieval, embeddings, and LLM reasoning together as one complete workflow. These types of frameworks help facilitate building RAG systems, but they do not remove the requirement for robust evaluation of RAG systems.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d081d9b elementor-widget elementor-widget-spacer\" data-id=\"d081d9b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e56b0f3 elementor-widget elementor-widget-menu-anchor\" data-id=\"e56b0f3\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"menu-anchor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-menu-anchor\" id=\"topic3\"><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b689af4 elementor-widget elementor-widget-heading\" data-id=\"b689af4\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">The Three Layers of RAG Evaluation<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-49cf8fc elementor-widget elementor-widget-image\" data-id=\"49cf8fc\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"1377\" height=\"751\" src=\"https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/the-three-layers-of-rag-evaluation.webp\" class=\"attachment-full size-full wp-image-4208\" alt=\"The Three Layers of RAG Evaluation\" srcset=\"https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/the-three-layers-of-rag-evaluation.webp 1377w, https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/the-three-layers-of-rag-evaluation-300x164.webp 300w, https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/the-three-layers-of-rag-evaluation-1024x558.webp 1024w, https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/the-three-layers-of-rag-evaluation-768x419.webp 768w\" sizes=\"(max-width: 1377px) 100vw, 1377px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f9bb329 elementor-widget elementor-widget-text-editor\" data-id=\"f9bb329\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Engineers usually evaluate RAG Systems based on three primary levels of measurement of performance:<\/span><\/p><ol><li><b> Retrieval Performance:<\/b><span style=\"font-weight: 400;\"> Retrieval Performance is a way to measure if the Knowledge Base produced relevant documents to use in the Language Model, and how those documents produced relevant results.<\/span><\/li><li><b> Generation Quality:<\/b><span style=\"font-weight: 400;\"> Generation Quality is a measure of how well the Language Model generates an answer to the query, based on the documents retrieved from the Knowledge Base.<\/span><\/li><li><b> End to End System Performance:<\/b><span style=\"font-weight: 400;\"> End to End System Performance is an evaluation of how well the entire system produced an output as an answer to the query.<\/span><\/li><\/ol><p><span style=\"font-weight: 400;\">Whenever an engineer evaluates the system, he must evaluate all three levels of performance simultaneously using a reliable method to accomplish this.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-619c694 elementor-widget elementor-widget-spacer\" data-id=\"619c694\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-858600e elementor-widget elementor-widget-menu-anchor\" data-id=\"858600e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"menu-anchor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-menu-anchor\" id=\"topic4\"><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0582de4 elementor-widget elementor-widget-heading\" data-id=\"0582de4\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Important Like How to Measure Retrieval Metrics<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b8141e3 elementor-widget elementor-widget-image\" data-id=\"b8141e3\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" width=\"1408\" height=\"768\" src=\"https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/key-retrieval-metrics-rag-system.webp\" class=\"attachment-full size-full wp-image-4212\" alt=\"key retrieval metrics RAG system\" srcset=\"https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/key-retrieval-metrics-rag-system.webp 1408w, https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/key-retrieval-metrics-rag-system-300x164.webp 300w, https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/key-retrieval-metrics-rag-system-1024x559.webp 1024w, https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/key-retrieval-metrics-rag-system-768x419.webp 768w\" sizes=\"(max-width: 1408px) 100vw, 1408px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-751da9d elementor-widget elementor-widget-text-editor\" data-id=\"751da9d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">How good a system is at retrieving relevant content from its database is determined by retrieval metrics.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d43b66a elementor-widget elementor-widget-heading\" data-id=\"d43b66a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">K-Level Precision<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2c4d9dd elementor-widget elementor-widget-text-editor\" data-id=\"2c4d9dd\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">K-level precision refers to how many of the returned entries at K-level are relevant. For example, K-level precision is 0.7 when an information retrieval system returns 10 total entries, of which 7 are relevant.<\/span><\/p><p><span style=\"font-weight: 400;\">This retrieval metric is particularly helpful when systems prioritize providing users with highly relevant material.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-886d3e9 elementor-widget elementor-widget-heading\" data-id=\"886d3e9\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">K-Level Recall<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-bfcf18c elementor-widget elementor-widget-text-editor\" data-id=\"bfcf18c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">K-level recall measures how many of the relevant documents returned were actually relevant in terms of what the user requested.<\/span><\/p><p><span style=\"font-weight: 400;\">A user with a high K-level recall will receive plenty of relevant content that was recently received by the information retrieval system and is necessary to create an appropriate response to the user&#8217;s inquiry.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-519cacc elementor-widget elementor-widget-heading\" data-id=\"519cacc\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Mean Reciprocal Rank<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7d9ca3e elementor-widget elementor-widget-text-editor\" data-id=\"7d9ca3e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Mean reciprocal rank (MRR) measures the rank position of the first relevant document in an ordered list of entries returned from an information retrieval system.<\/span><\/p><p><span style=\"font-weight: 400;\">The faster a user receives the first correct entry, the better the user determines that the information retrieval system is working the way it should.<\/span><\/p><p><span style=\"font-weight: 400;\">This is especially important when a large component of the system relies on returning entries from the top portion of the list.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4e93fdb elementor-widget elementor-widget-heading\" data-id=\"4e93fdb\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">nDCG (Normalized Discounted Cumulative Gain)<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-96e9ffa elementor-widget elementor-widget-text-editor\" data-id=\"96e9ffa\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">nDCG assesses the quality of ranking retrieved documents based on where relevant documents are located. Therefore, this measure is common in the evaluation of search engines due to its consideration of the importance of both relevance and order of the ranked items.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7925a59 elementor-widget elementor-widget-heading\" data-id=\"7925a59\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Context Precision and Context Recall<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-bc614e2 elementor-widget elementor-widget-text-editor\" data-id=\"bc614e2\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">These two metrics were created solely for the purpose of evaluating systems that employ RAG. They provide information about whether or not the retrieved context contains content that can be used to derive a correct reply to questions. Multiple studies have shown that the improvement of context precision significantly decreases hallucinations in RAG-generated replies.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-571bd4c elementor-widget elementor-widget-spacer\" data-id=\"571bd4c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-784aeb0 elementor-widget elementor-widget-menu-anchor\" data-id=\"784aeb0\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"menu-anchor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-menu-anchor\" id=\"topic5\"><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0752b85 elementor-widget elementor-widget-heading\" data-id=\"0752b85\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Generation Metrics That Actually Matter<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8a16323 elementor-widget elementor-widget-image\" data-id=\"8a16323\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1408\" height=\"768\" src=\"https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/how-generation-quality-evaluated-rag-systems.webp\" class=\"attachment-full size-full wp-image-4216\" alt=\"how generation quality evaluated RAG systems\" srcset=\"https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/how-generation-quality-evaluated-rag-systems.webp 1408w, https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/how-generation-quality-evaluated-rag-systems-300x164.webp 300w, https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/how-generation-quality-evaluated-rag-systems-1024x559.webp 1024w, https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/how-generation-quality-evaluated-rag-systems-768x419.webp 768w\" sizes=\"(max-width: 1408px) 100vw, 1408px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9b7d085 elementor-widget elementor-widget-text-editor\" data-id=\"9b7d085\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">After retrieving the appropriate documents, an evaluation of the quality of the generated output should be undertaken.<\/span><\/p><p><span style=\"font-weight: 400;\">Many Retrieval Augmented Generation (RAG) systems leverage large language models such as GPT to generate answers based on retrieved context from past documents.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1a77f07 elementor-widget elementor-widget-text-editor\" data-id=\"1a77f07\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><b>Faithfulness<\/b><span style=\"font-weight: 400;\">: Faithfulness assesses whether a generated response is grounded in the obtained documents.<\/span><\/p><p><span style=\"font-weight: 400;\">If a generated response contains information that is not represented anywhere in the retrieved context, the model is likely generating hallucinations.<\/span><\/p><p><b>Relevance of the Answer:<\/b> <span style=\"font-weight: 400;\">This metric evaluates how well a generated response answers the user\u2019s request\/question.<\/span><\/p><p><span style=\"font-weight: 400;\">Even if a generated response is factually correct, it may not be relevant to the question that was asked<\/span><\/p><p><b>Correctness of Answer:<\/b> <span style=\"font-weight: 400;\">Correctness of answer evaluates whether the generated output is factual.<\/span><\/p><p><span style=\"font-weight: 400;\">Many times, expertise and\/or reference answers are used to evaluate correctness of the generated output.<\/span><\/p><p><b>Hallucination Rate: <\/b><span style=\"font-weight: 400;\">Hallucination is the term used to describe the experience of a language model generating content that is invalid according to the retrieved documents.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-de1a819 elementor-widget elementor-widget-text-editor\" data-id=\"de1a819\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">One of the major objectives of RAG architectures is to decrease the number of hallucinations produced by the language model.<\/span><\/p><p><span style=\"font-weight: 400;\">The decision to use retrieval as opposed to base model&#8217;s knowledge can be very difficult to make. A discussion of retrieval-based vs fine-tuning systems was done in an earlier article regarding the use of retrieval in production environments; thus, if you are interested in this topic and want more information about how system design affects evaluation, you might benefit from reading the discussion in <\/span><em><span style=\"text-decoration: underline;\"><a href=\"https:\/\/proleed.academy\/blog\/rag-vs-fine-tuning-what-works-better-in-real-products\/\"><b>RAG versus Fine-tuning: Which Works Best for Real World Applications?<\/b><\/a><\/span><\/em><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3deb0bc elementor-widget elementor-widget-spacer\" data-id=\"3deb0bc\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f7bfce5 elementor-widget elementor-widget-menu-anchor\" data-id=\"f7bfce5\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"menu-anchor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-menu-anchor\" id=\"topic6\"><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2a944b1 elementor-widget elementor-widget-heading\" data-id=\"2a944b1\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">End-to-End RAG System Metrics<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0b76f43 elementor-widget elementor-widget-image\" data-id=\"0b76f43\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1408\" height=\"768\" src=\"https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/end-to-end-rag-system-metrics.webp\" class=\"attachment-full size-full wp-image-4220\" alt=\"End-to-End RAG System Metrics\" srcset=\"https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/end-to-end-rag-system-metrics.webp 1408w, https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/end-to-end-rag-system-metrics-300x164.webp 300w, https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/end-to-end-rag-system-metrics-1024x559.webp 1024w, https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/end-to-end-rag-system-metrics-768x419.webp 768w\" sizes=\"(max-width: 1408px) 100vw, 1408px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-db6e203 elementor-widget elementor-widget-text-editor\" data-id=\"db6e203\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Apart from Measuring the Retrieval and Generation Metrics, Engineer&#8217;s Must Consider Overall System Performance.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3a27c65 elementor-widget elementor-widget-heading\" data-id=\"3a27c65\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Exact Match (EM)<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d4e57ee elementor-widget elementor-widget-text-editor\" data-id=\"d4e57ee\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Exact Match (EM) Measures whether or not the generated answer is exactly the same as the expected answer.<\/span><\/p><p><span style=\"font-weight: 400;\">The Exact Match is commonly used as a metric of performance in Question Answering Systems.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-8a1bb15 elementor-widget elementor-widget-heading\" data-id=\"8a1bb15\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">F1 Score<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-62414ad elementor-widget elementor-widget-text-editor\" data-id=\"62414ad\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">F1 Score is the average of Precision and Recall and Measures how much the Generated Answer and the Reference Answer Overlap.<\/span><\/p><p><span style=\"font-weight: 400;\">F1 Scores are helpful when EM&#8217;s are too strict to be used for Evaluation.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-cd2e810 elementor-widget elementor-widget-heading\" data-id=\"cd2e810\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Semantic Similarity Scores<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-55bf082 elementor-widget elementor-widget-text-editor\" data-id=\"55bf082\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">Similarity Metrics measure whether or not the generated answer Conveyed the Same Meaning as the Reference Answer, even if different Wording is Used.<\/span><\/p><p><span style=\"font-weight: 400;\">Similarity Metrics are used to Evaluate Open-ended Responses.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7189774 elementor-widget elementor-widget-heading\" data-id=\"7189774\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">Latency and Response Time<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6de9607 elementor-widget elementor-widget-text-editor\" data-id=\"6de9607\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">In Production Systems, Performance is not just about producing Accurate Results.<\/span><\/p><p><span style=\"font-weight: 400;\">The Response time is an Important aspect of User&#8217;s experience as Well. RAG must Retrieve Documents, process Context, and Produce an Answer Quick Enough to Be Used Real-time.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-69a702d elementor-widget elementor-widget-spacer\" data-id=\"69a702d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3a05f21 elementor-widget elementor-widget-menu-anchor\" data-id=\"3a05f21\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"menu-anchor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-menu-anchor\" id=\"topic7\"><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-0eab5f7 elementor-widget elementor-widget-heading\" data-id=\"0eab5f7\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">LLM-Based Evaluation Approaches<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-bea8b5b elementor-widget elementor-widget-image\" data-id=\"bea8b5b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1408\" height=\"768\" src=\"https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/llm-based-evaluation-approaches.webp\" class=\"attachment-full size-full wp-image-4224\" alt=\"LLM-Based Evaluation Approaches\" srcset=\"https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/llm-based-evaluation-approaches.webp 1408w, https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/llm-based-evaluation-approaches-300x164.webp 300w, https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/llm-based-evaluation-approaches-1024x559.webp 1024w, https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/llm-based-evaluation-approaches-768x419.webp 768w\" sizes=\"(max-width: 1408px) 100vw, 1408px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4089123 elementor-widget elementor-widget-text-editor\" data-id=\"4089123\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">New evaluation techniques are being researched that leverage the capabilities of language models.<\/span><\/p><p><span style=\"font-weight: 400;\">LLM-as-a-judge<\/span><\/p><p><span style=\"font-weight: 400;\">Here, an LLM serves to evaluate the response quality that was generated by another LLM.<\/span><\/p><p><span style=\"font-weight: 400;\">Evaluations consist of three major components:<\/span><\/p><ul><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Correctness;<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Relevance; and<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Faithfulness.<\/span><\/li><\/ul><p><span style=\"font-weight: 400;\">This approach is increasingly common because it enables a scalable form of evaluation without the associated costs of large amounts of human annotation.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-b374724 elementor-widget elementor-widget-text-editor\" data-id=\"b374724\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><b>Pairwise Answer Comparison<\/b><\/p><p><span style=\"font-weight: 400;\">In this evaluation method, two sample generated answers are compared, and an evaluator (either human or an LLM) is asked which answer is better.<\/span><\/p><p><span style=\"font-weight: 400;\">This method is popular as an evaluation method, both for benchmarking different LLMs against each other as well as for conducting A\/B testing within an LLM.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e5be3da elementor-widget elementor-widget-spacer\" data-id=\"e5be3da\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e7158e6 elementor-widget elementor-widget-menu-anchor\" data-id=\"e7158e6\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"menu-anchor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-menu-anchor\" id=\"topic8\"><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-1e4117c elementor-widget elementor-widget-heading\" data-id=\"1e4117c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Common Mistakes When Evaluating RAG Systems\n<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-055c5a1 elementor-widget elementor-widget-text-editor\" data-id=\"055c5a1\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">RAG evaluation can be difficult for teams since they are often concerned about the wrong metrics.<\/span><\/p><p><span style=\"font-weight: 400;\">Some common pitfalls are:<\/span><\/p><p><b>Evaluating just the generated response &#8211; <\/b><span style=\"font-weight: 400;\">If you overlook the quality of your retrieval, you are missing out on potential major failures within your system.<\/span><\/p><p><b>Disregarding retrieval performance &#8211; <\/b><span style=\"font-weight: 400;\">Even the best language models will fail to produce an accurate answer without the right context to generate an answer.<\/span><\/p><p><b>Putting too much emphasis on one metric &#8211; <\/b><span style=\"font-weight: 400;\">Evaluating RAG requires evaluating a range of metrics at a variety of levels.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-6283c4d elementor-widget elementor-widget-spacer\" data-id=\"6283c4d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-71daa65 elementor-widget elementor-widget-menu-anchor\" data-id=\"71daa65\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"menu-anchor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-menu-anchor\" id=\"topic9\"><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-25b3491 elementor-widget elementor-widget-heading\" data-id=\"25b3491\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Best Practices for Reliable RAG Evaluation\n<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ea85aea elementor-widget elementor-widget-image\" data-id=\"ea85aea\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1408\" height=\"768\" src=\"https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/best-practices-for-reliable-rag-evaluation.webp\" class=\"attachment-full size-full wp-image-4228\" alt=\"Best Practices for Reliable RAG Evaluation\" srcset=\"https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/best-practices-for-reliable-rag-evaluation.webp 1408w, https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/best-practices-for-reliable-rag-evaluation-300x164.webp 300w, https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/best-practices-for-reliable-rag-evaluation-1024x559.webp 1024w, https:\/\/proleed.academy\/blog\/wp-content\/uploads\/2026\/03\/best-practices-for-reliable-rag-evaluation-768x419.webp 768w\" sizes=\"(max-width: 1408px) 100vw, 1408px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3975987 elementor-widget elementor-widget-text-editor\" data-id=\"3975987\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">In creating a trustworthy evaluation process, the majority of AI teams will use some combination of the following methods to evaluate their models:<\/span><\/p><ul><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Use multiple layers of evaluation methods over time (eg. Retrieval level evaluations, Generation level evaluations &amp; End-To-End evaluations).<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Use both automated and human evaluation methods to evaluate the same model. Automated measures can provide a scale for measuring performance whereas human evaluation provides a measure of reliability for a model.<\/span><\/li><li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Review and improve the evaluation on an ongoing basis as new information is added to the knowledge base of the RAG system.<\/span><\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-67bab5a elementor-widget elementor-widget-spacer\" data-id=\"67bab5a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-34fca8e elementor-widget elementor-widget-menu-anchor\" data-id=\"34fca8e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"menu-anchor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-menu-anchor\" id=\"topic10\"><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-73f7c54 elementor-widget elementor-widget-heading\" data-id=\"73f7c54\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Conclusion<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f03f9a5 elementor-widget elementor-widget-text-editor\" data-id=\"f03f9a5\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><span style=\"font-weight: 400;\">The evaluation of RAG systems demands an extensive approach that cannot be replicated when evaluating standard machine learning models. This is due to the fact that RAG architectures incorporate both retrieval and generation components and so require that engineers evaluate performance on many different layers in order to fully understand how the system works.<\/span><\/p><p><span style=\"font-weight: 400;\">Metrics like Precision@K, Recall@K, MRR, fidelity, hallucination rate, and end-to-end performance metrics are useful to help determine how effectively a RAG system functions in the real world.<\/span><\/p><p><span style=\"font-weight: 400;\">For AI engineers constructing production-ready systems, it is imperative to become proficient with these evaluation methods; a properly designed RAG architecture will significantly enhance knowledge-based AI applications, but only if it is evaluated for performance on an ongoing basis.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-f8ea010 elementor-widget elementor-widget-spacer\" data-id=\"f8ea010\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"spacer.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-spacer\">\n\t\t\t<div class=\"elementor-spacer-inner\"><\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a95b2ab elementor-widget elementor-widget-menu-anchor\" data-id=\"a95b2ab\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"menu-anchor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-menu-anchor\" id=\"topic11\"><\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ba08421 elementor-widget elementor-widget-heading\" data-id=\"ba08421\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Frequently Asked Questions \n<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-efc40fb elementor-widget elementor-widget-accordion\" data-id=\"efc40fb\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"accordion.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t<div class=\"elementor-accordion\">\n\t\t\t\t\t\t\t<div class=\"elementor-accordion-item\">\n\t\t\t\t\t<div id=\"elementor-tab-title-2511\" class=\"elementor-tab-title\" data-tab=\"1\" role=\"button\" aria-controls=\"elementor-tab-content-2511\" aria-expanded=\"false\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon elementor-accordion-icon-right\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon-closed\"><i class=\"fas fa-plus\"><\/i><\/span>\n\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon-opened\"><i class=\"fas fa-minus\"><\/i><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-accordion-title\" tabindex=\"0\">What is the most effective way to assess RAG outside of the one single measure of evaluation?  <\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div id=\"elementor-tab-content-2511\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"1\" role=\"region\" aria-labelledby=\"elementor-tab-title-2511\">There is no single measure of evaluation; in fact, the best way to evaluate RAG is through several measures: how well you retrieve information, how well you generate it, and system function (how well all parts work together).<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"elementor-accordion-item\">\n\t\t\t\t\t<div id=\"elementor-tab-title-2512\" class=\"elementor-tab-title\" data-tab=\"2\" role=\"button\" aria-controls=\"elementor-tab-content-2512\" aria-expanded=\"false\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon elementor-accordion-icon-right\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon-closed\"><i class=\"fas fa-plus\"><\/i><\/span>\n\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon-opened\"><i class=\"fas fa-minus\"><\/i><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-accordion-title\" tabindex=\"0\">What makes traditional NLP measures inadequate for evaluating RAG?<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div id=\"elementor-tab-content-2512\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"2\" role=\"region\" aria-labelledby=\"elementor-tab-title-2512\">Traditional NLP measures focus on how well you generate text, while RAG is dependent on accurately retrieving the appropriate information; thus, a different type of measure will need to be employed.<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"elementor-accordion-item\">\n\t\t\t\t\t<div id=\"elementor-tab-title-2513\" class=\"elementor-tab-title\" data-tab=\"3\" role=\"button\" aria-controls=\"elementor-tab-content-2513\" aria-expanded=\"false\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon elementor-accordion-icon-right\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon-closed\"><i class=\"fas fa-plus\"><\/i><\/span>\n\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon-opened\"><i class=\"fas fa-minus\"><\/i><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-accordion-title\" tabindex=\"0\">What is the current method of measuring RAG hallucinations & how does it differ from other hallucinations by other NLP models?<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div id=\"elementor-tab-content-2513\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"3\" role=\"region\" aria-labelledby=\"elementor-tab-title-2513\">Hallucinations are measured using faithfulness scores and LSME (metric semantic) evaluation; state-of-the-art LLMs use metrics that relate to similar frameworks of evaluation.<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"elementor-accordion-item\">\n\t\t\t\t\t<div id=\"elementor-tab-title-2514\" class=\"elementor-tab-title\" data-tab=\"4\" role=\"button\" aria-controls=\"elementor-tab-content-2514\" aria-expanded=\"false\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon elementor-accordion-icon-right\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon-closed\"><i class=\"fas fa-plus\"><\/i><\/span>\n\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon-opened\"><i class=\"fas fa-minus\"><\/i><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-accordion-title\" tabindex=\"0\">What is the difference between retrieval metrics versus generation metrics?<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div id=\"elementor-tab-content-2514\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"4\" role=\"region\" aria-labelledby=\"elementor-tab-title-2514\">Retrieval metrics can be defined as assessing whether you have retrieved a good corresponding document, while generation metrics assess how closely you generate correct and appropriate answers\/responses compared to corresponding documents.<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t<div class=\"elementor-accordion-item\">\n\t\t\t\t\t<div id=\"elementor-tab-title-2515\" class=\"elementor-tab-title\" data-tab=\"5\" role=\"button\" aria-controls=\"elementor-tab-content-2515\" aria-expanded=\"false\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon elementor-accordion-icon-right\" aria-hidden=\"true\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon-closed\"><i class=\"fas fa-plus\"><\/i><\/span>\n\t\t\t\t\t\t\t\t<span class=\"elementor-accordion-icon-opened\"><i class=\"fas fa-minus\"><\/i><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t<a class=\"elementor-accordion-title\" tabindex=\"0\">Do LLMs have the ability to measure any output produced by other LLMs?<\/a>\n\t\t\t\t\t<\/div>\n\t\t\t\t\t<div id=\"elementor-tab-content-2515\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"5\" role=\"region\" aria-labelledby=\"elementor-tab-title-2515\">Yes. There are many current measurement techniques in the LLM community involving LLMs as replaced evaluation agents who are assessing the quality of provide an answer generated from one LLM to another.<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Table of contents Introduction What Is RAG Evaluation? Understanding the RAG Evaluation Problem The Three Layers of RAG Evaluation Important [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":4203,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[7],"tags":[],"class_list":["post-4123","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-artificial-intelligence"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.2 - 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