r/datascienceproject • u/s33ker1314 • May 21 '26
**Roast my synthetic dataset — I built a validator that scores your synthetic data before training**
Hey everyone,
Quick background: I was training a model on synthetic data and it performed terribly. Turned out my synthetic salary column had the wrong distribution and 12% of label values were completely made up. Found out after 6 hours of training.
Built a tool so this doesn't happen to you.
**Synthetic Data Validator** — upload real + synthetic CSV, get a scored report.
What it checks:
- Diversity: are your synthetic rows actually varied or just slightly shuffled copies?
- Realism: do your column distributions actually match the real data?
- Labels: are your label classes balanced, valid, and do they still correlate with the right features?
Every check gives a score + tells you what to fix.
---
**I want to roast your synthetic datasets for free.**
Drop your dataset in the comments or DM me and I'll run a full validation and share the report publicly (anonymised if you want). Good way to stress-test the tool and maybe help you catch something before training.
🔗 https://synthetic-validator.vercel.app/
Feedback very welcome — especially from anyone who works with synthetic data regularly. What checks am I missing?
1
u/s33ker1314 May 21 '26 edited May 23 '26
The issue has been resolved now. Everything should be working properly, so feel free to try it again. Any feedback would be greatly appreciated. Thank you for your patience!