rishhh/verisci-claim-verifier-dense-adapted-seed123
VeriSci Claim Verifier Dense-Retrieval-Adapted Candidate
Dense-retrieval-adapted VeriSci classifier for scientific claim verification over SUPPORTS, REFUTES, and NOT_ENOUGH_INFO.
Promotion Status
Not promoted. This checkpoint was trained and evaluated successfully, but it regressed against rishhh/verisci-claim-verifier-retrieval-adapted-seed123 on both the derived test split and the dense/hybrid retrieval-grounded SciFact validation gate.
Training Data
allenai/scifact_entailmenttrain split with gold evidence sentences.allenai/scifacttrain claims converted into gold evidence snippets, BM25-selected evidence snippets, and BM25-retrieved hardNOT_ENOUGH_INFOnegatives.andreiaalexa/scifact-relevance-pairstitle/train hard negatives.
Derived Test
Accuracy: 0.8935 Macro F1: 0.8567
Full SciFact Validation Gate
Top-1 end-to-end accuracy: 0.5711 Top-1 end-to-end macro F1: 0.5536 Top-5 decisive accuracy: 0.6356 Top-5 decisive macro F1: 0.5935
Dense/Hybrid Retrieval-Grounded Gate
Using rishhh/verisci-scifact-e5-retriever, hybrid alpha 0.75, and guarded top-5 decisive aggregation:
- Accuracy: 0.6756
- Macro F1: 0.6426
The current promoted retrieval-adapted verifier reaches 0.6911 accuracy and 0.6529 macro F1 under the same dense/hybrid guarded gate.
See evaluation/eval_summary.json for full metrics and limitations.
Responsible Use
This model is not a medical device, not a substitute for peer review, and should not be used for clinical, legal, or public-policy decisions without expert review.
