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Racing GPU training

Train the greyhound learning-to-rank ranker on the GPU (RTX 3090 Ti, XGBoost device=cuda). Elixir builds the parity-tested feature matrix over the window, trains on the GPU, then registers a model run the Board serves. Runs as a background job (visible in Jobs) on the GPU node.

Blank window spans the whole warehouse (4yr GH history).

Model runs
TB_rank_ndcg_1783350136000 TB 0.2201 142633 13711 trained 2026-07-06 15:02
TB_rank_ndcg_1783344946000 TB 0.8958 1669 160 trained 2026-07-06 13:35
TB_rank_ndcg_1783343508000 TB 0.8472 1669 160 trained 2026-07-06 13:11
TB_rank_ndcg_1783341349000 TB 0.8333 1669 160 trained 2026-07-06 12:35
TB_rank_ndcg_1783339624000 TB 0.8264 1669 160 trained 2026-07-06 12:07
TB_rank_ndcg_1783338264000 TB 0.5903 1669 160 trained 2026-07-06 11:44
GH_rank_ndcg_4yr_1783271234000 GH 0.3478 161004 22994 trained 2026-07-05 17:07
GH_rank_ndcg_1783213783000 GH 0.5559 129771 18530 trained 2026-07-05 01:09
GH_rank_ndcg_1783184504000 GH 0.7194 20363 2559 trained 2026-07-04 17:01
GH_rank_ndcg_1782871790000 GH 0.9870 1842 230 trained 2026-07-01 02:09
GH_rank_ndcg_1782835364000 GH 0.6454 9916 1198 trained 2026-06-30 16:02
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