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submission_exp116_lgbm6_nocs_B.ziptalkpl-ai/TalkPlayData-Challenge-*). No external data is used. The models are fully retrainable from scratch with the commands in the code repository README; these files are published for transparency and for direct verification without retraining.| File | Role |
|---|---|
stage1_anchor/lgbm_B_ll_top500.txt | Stage-1 BM25-anchor ranker. LightGBM binary logloss over the top-500 RRF union of 4 BM25 views + 4 exact-match fields (config exp015_B_ll_t500_B.yaml, source profile B). Referenced by reranker_model_name in that config. |
stage2_reranker_lgbm6_nocs/lgbm_lambdarank_seed2026061{6..21}.txt | Stage-2 reranker of the selected final submission: 6 LightGBM LambdaRank boosters (seeds 20260616 to 20260621). Trained on the Dev split candidate union (12 sources, cross_session dropped): 2,949,717 candidate rows, 4,333 positive groups, 73 rank-based features, num_boost_round=450, num_leaves=31, min_data_in_leaf=80, lambda_l2=8.0, learning_rate=0.03, deterministic=true. Raw scores of the 6 boosters are averaged, then the top-20 per session-turn is taken. |
build_features in mcrs/experiments/exp027_wide_source_lgbm/rank_source_lgbm_mixed_topk.py of the code repository.1import lightgbm as lgb
2
3booster = lgb.Booster(model_file="stage2_reranker_lgbm6_nocs/lgbm_lambdarank_seed20260616.txt")
4scores = booster.predict(x) # x: [n_candidates, 73] built by build_features()deterministic=true, fixed seeds, fixed thread count). The published boosters were regenerated with the exact final-run command path and verified against the original run artifacts tracked in the code repository:0.25870485648368946 exactly.