yolov8-train-loop
yolov8-train-loop is a Model training & evaluation skill for AI agents, published by KeploreAI-Lab in the MindAct repository on GitHub. Skillspace rates yolov8-train-loop D (66/100) and it passed the safety scan; the rating is based on static analysis only.
Use this skill to run a full iterative training improvement loop for YOLOv8 (or YOLOv8-seg) models — from first analysis through repeated train→validate→diagnose→improve cycles until a target metric is reached. This skill is the "improve and iterate" complement to yolov8-industrial-finetune (which covers one-shot setup). Trigger this skill when the user says: "improve my model", "not reaching target accuracy", "mAP is too low", "how do I get better results", "train and keep improving", "full training pipeline", "training loop", "iterate until target", "diagnose why my model is bad", "training plan", "my model is not converging", or any time a user wants a structured repeatable improvement process rather than a single training run.
- Grade
- D
- Quality
- 66 / 100
- Safety
- Passed
- GitHub stars
- 85
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 84 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- AGPL-3.0
- Adoption
- Adopted by 1 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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