From 7367e82f4090642433b135ac94079151c7b075b5 Mon Sep 17 00:00:00 2001 From: Ikko Eltociear Ashimine Date: Sat, 9 Mar 2024 04:06:39 +0900 Subject: [PATCH] Update building_evals.ipynb multipe -> multiple --- misc/building_evals.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/misc/building_evals.ipynb b/misc/building_evals.ipynb index 3d52814..f9987c7 100644 --- a/misc/building_evals.ipynb +++ b/misc/building_evals.ipynb @@ -374,7 +374,7 @@ "Now you know about different grading design patterns for evals, and are ready to start building your own. As you do, here are a few guiding pieces of wisdom to get you started.\n", "- Make your evals specific to your task whenever possible, and try to have the distribution in your eval represent ~ the real life distribution of questions and question difficulties.\n", "- The only way to know if a model-based grader can do a good job grading your task is to try. Try it out and read some samples to see if your task is a good candidate.\n", - "- Often all that lies between you and an automatable eval is clever design. Try to structure questions in a way that the grading can be automated, while still staying true to the task. Reformatting questions into multipe choice is a common tactic here.\n", + "- Often all that lies between you and an automatable eval is clever design. Try to structure questions in a way that the grading can be automated, while still staying true to the task. Reformatting questions into multiple choice is a common tactic here.\n", "- In general, your preference should be for higher volume and lower quality of questions over very low volume with high quality." ] }