Models
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None active
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No personal embedding trained yet
Performance
Open analytics dashboard ↗No model history yet. Performance ribbon will appear after the first train.
Training
Run these in order whenever your cohort has changed materially (new approveds, new rejected_seed imports, large vetting batch committed). Each step feeds the next.
Contrastive (personal embedding)
Learns a 256-dim space where approveds cluster apart from rejecteds from your swipe history. LightGBM consumes this as a feature, so it must be retrained first.
LightGBM (ranker)
Trains the approve/reject classifier on the updated personal embedding + foundation features. New row appears below with overall accuracy, rejected recall, AUC, and gate.
Re-evaluate vetting
Re-scores every candidate currently in the vetting queue against the freshly-trained models. Runs in the background — vetting queue refreshes as decisions update.
Re-evaluate spring clean
Re-scores every flagged profile in the existing pool against the freshly-trained models. Independent of step 3 — they can run in either order or in parallel.
LightGBM history
No LightGBM models trained yet.
Contrastive adapter history
No contrastive models trained yet.
Couldn't reach the pipeline. Check health.