From 7a5e88c2e61f25fb619a683344e58e663688b924 Mon Sep 17 00:00:00 2001 From: Paul Gauthier Date: Mon, 6 May 2024 11:58:16 -0700 Subject: [PATCH] finishing row.percent_cases_well_formed --- docs/leaderboards/index.md | 21 +++++++++++++++------ 1 file changed, 15 insertions(+), 6 deletions(-) diff --git a/docs/leaderboards/index.md b/docs/leaderboards/index.md index 3e64f0226..8ce72b7b5 100644 --- a/docs/leaderboards/index.md +++ b/docs/leaderboards/index.md @@ -19,13 +19,19 @@ to help users select which models to use with aider. While [aider can connect to almost any LLM](/docs/llms.html) it will work best with models that score well on the benchmarks. +The key benchmarking results are: + +- **Percent completed** - Measures what percentage of the coding tasks that the LLM completed successfully. To complete a task, the LLM must solve the programming assignment *and* edit the code to implement that solution. +- **Percent without edit errors** - Measures the percent of coding tasks that the LLM completed without making any mistakes in the code editing format. If the LLM makes edit mistakes, aider will give it feedback and ask for a fixed copy of the edit. But the best models can reliably conform to the edit format, without making errors. + ## Code editing leaderboard - + + @@ -36,6 +42,7 @@ it will work best with models that score well on the benchmarks. + @@ -51,14 +58,14 @@ it will work best with models that score well on the benchmarks. var leaderboardData = { labels: [], datasets: [{ - label: 'Percent correct on code editing tasks', + label: 'Percent coding tasks solved', data: [], backgroundColor: 'rgba(54, 162, 235, 0.2)', borderColor: 'rgba(54, 162, 235, 1)', borderWidth: 1 }, { - label: 'Percent cases well formed', + label: 'Percent completed without edit errors', data: [], backgroundColor: 'rgba(255, 99, 132, 0.2)', borderColor: 'rgba(255, 99, 132, 1)', @@ -101,7 +108,8 @@ Therefore, results are available for fewer models. - + + @@ -112,6 +120,7 @@ Therefore, results are available for fewer models. + @@ -127,14 +136,14 @@ Therefore, results are available for fewer models. var leaderboardData = { labels: [], datasets: [{ - label: 'Percent correct on code refactoring tasks', + label: 'Percent coding tasks solved', data: [], backgroundColor: 'rgba(54, 162, 235, 0.2)', borderColor: 'rgba(54, 162, 235, 1)', borderWidth: 1 }, { - label: 'Percent cases well formed', + label: 'Percent completed without edit errors', data: [], backgroundColor: 'rgba(255, 99, 132, 0.2)', borderColor: 'rgba(255, 99, 132, 1)',
ModelPercent correctPercent completedPercent without edit errors Command Edit format
{{ row.model }} {{ row.pass_rate_2 }}%{{ row.percent_cases_well_formed }}% {{ row.command }} {{ row.edit_format }}
ModelPercent correctPercent completedPercent without edit errors Command Edit format
{{ row.model }} {{ row.pass_rate_1 }}%{{ row.percent_cases_well_formed }}% {{ row.command }} {{ row.edit_format }}