Elib27/conventional-commits

Git Diff → Conventional Commit Messages

A dataset of 12,433 (git diff, commit message) pairs scraped from real open-source TypeScript repositories, filtered for quality and formatted for fine-tuning small language models to generate Conventional Commits.

Built as part of a project to fine-tune a local LLM to write commit messages as a prepare-commit-msg git hook. Full write-up: eliotbas.com/projects/commits-fine-tuning

Dataset details

Source repositories

13 open-source TypeScript repositories selected for commit discipline and diversity:

• —Libraries: Vite, Vitest, Vue.js core, Angular, tRPC, TanStack Query
• —Apps/platforms: Supabase, Nuxt, Twenty, Prisma, TypeORM
• —Tooling: typescript-eslint, commitlint
• —Workflow-specific: Botpress OSS (to match the author's internship codebase)

Format

JSONL, chat format. Each example has a messages field with two turns:

{
  "messages": [
    {
      "role": "user",
      "content": "diff --git a/src/index.ts b/src/index.ts\n..."
    },
    {
      "role": "assistant",
      "content": "feat(core): add retry logic for failed requests"
    }
  ],
  "meta": {
    "repo": "vitejs/vite",
    "hash": "496a63ad5af3b9e5a7bba5477057f1e61a267a70"
  }
}

Filtering and quality criteria

Not every commit was kept. The main filters applied:

• —Conventional Commits enforcement — message must match type(scope)?: description format
• —Trailing ref stripping — (#1234) references removed; not inferable from the diff and would be learned as hallucination fodder
• —Generated-file exclusion — each commit must touch at least one non-generated file (lockfiles, minified JS, dist/, snapshots excluded)
• —Per-repo cap — prevents large repos (e.g. Angular) from dominating the distribution
• —Length filter — too small and too big commits are filtered

Commit type distribution

Key statistics

Intended use

Designed for LoRA fine-tuning of small code language models (0.5B–3B parameters) on the task of generating a single Conventional Commit message from a git diff --staged output.

Models fine-tuned on this dataset were evaluated in the accompanying article. Best results with:

• —Qwen2.5-Coder-0.5B-Instruct
• —Qwen2.5-Coder-1.5B-Instruct
• —Qwen2.5-Coder-3B-Instruct

Limitations

• —TypeScript-specific: sourced entirely from TypeScript repos; may not generalize to other languages or mixed codebases
• —High-discipline repos only: all source repos follow Conventional Commits strictly; behavior on messier codebases is untested
• —Diff-only context: the model sees only the diff, not the ticket, PR description, or broader codebase context — the human author always had more information

Related resources

• —Article: eliotbas.com/projects/commits-fine-tuning
• —GitHub (scraping scripts, training and evaluation code, git hook): github.com/Elib27/commits-fine-tune
• —Fine-tuned models: (HuggingFace model links)