•1 min read•from Machine Learning
Free tool I built to score dataset quality (LQS) — feedback welcome [D]
Our take
We are excited to introduce our free Label Quality Score (LQS) tool designed to enhance dataset quality in our marketplace. This user-friendly tool allows you to upload datasets in various formats, including CSV, Parquet, JSONL, COCO JSON, and YOLO, providing a comprehensive score from 0 to 100 across seven dimensions. Each score highlights specific issues affecting quality. We invite feedback from dataset professionals to ensure our scoring system meets your needs. Join the conversation about our methodology in the comments. Discover more at labelsets.ai/quality-audit.
We built a Label Quality Score (LQS) system for our dataset marketplace and opened it up as a free standalone tool.
Upload a dataset → get a 0–100 score broken down across 7 dimensions with specific flags for what's degrading quality.
Supports CSV, Parquet, JSONL, COCO JSON, YOLO — most common ML formats.
Link: labelsets.ai/quality-audit
Not trying to pitch anything, genuinely want to know if the scoring makes sense to people who work with datasets professionally. Happy to discuss the methodology in comments.
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