From 1714f334180a4935a8858e557b90b303b1635b29 Mon Sep 17 00:00:00 2001 From: Ayaka-mogumogu Date: Sun, 9 Feb 2025 23:49:04 +0100 Subject: [PATCH] docs: fix semantic similarity description (cross-encoder -> bi-encoder) --- docs/concepts/metrics/available_metrics/semantic_similarity.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/concepts/metrics/available_metrics/semantic_similarity.md b/docs/concepts/metrics/available_metrics/semantic_similarity.md index 29f98fc19..174c4de46 100644 --- a/docs/concepts/metrics/available_metrics/semantic_similarity.md +++ b/docs/concepts/metrics/available_metrics/semantic_similarity.md @@ -2,7 +2,7 @@ The concept of Answer Semantic Similarity pertains to the assessment of the semantic resemblance between the generated answer and the ground truth. This evaluation is based on the `ground truth` and the `answer`, with values falling within the range of 0 to 1. A higher score signifies a better alignment between the generated answer and the ground truth. -Measuring the semantic similarity between answers can offer valuable insights into the quality of the generated response. This evaluation utilizes a cross-encoder model to calculate the semantic similarity score. +Measuring the semantic similarity between answers can offer valuable insights into the quality of the generated response. This evaluation utilizes a bi-encoder model to calculate the semantic similarity score. ### Example