RovOpt/nohup.out

[LightGBM] [Warning] min_data_in_leaf is set=60, min_child_samples=30 will be ignored. Current value: min_data_in_leaf=60
[LightGBM] [Warning] min_data_in_leaf is set=60, min_child_samples=30 will be ignored. Current value: min_data_in_leaf=60
[LightGBM] [Warning] min_data_in_leaf is set=60, min_child_samples=30 will be ignored. Current value: min_data_in_leaf=60
[LightGBM] [Warning] min_data_in_leaf is set=60, min_child_samples=30 will be ignored. Current value: min_data_in_leaf=60
stage 1: time cost : 0.12420 sec
stage 2: time cost : 0.12090 sec
stage 3: time cost : 0.12970 sec
stage 4: time cost : 0.13302 sec
stage 1: time cost : 0.00954 sec
stage 2: time cost : 0.00869 sec
stage 3: time cost : 0.00879 sec
stage 4: time cost : 0.00902 sec
value feature generate successfully
videoid feature generate successfully
lenth tag_dict: 47609
tag tfidf feature generate successfully
tag dimension: 59393
lenth words_dict: 189467
tag tfidf feature generate successfully
words dimension: 59390
folds 0
Training until validation scores don't improve for 200 rounds
[100]	training's rmse: 0.226424	valid_1's rmse: 0.225884
[200]	training's rmse: 0.0973668	valid_1's rmse: 0.0971656
[300]	training's rmse: 0.057936	valid_1's rmse: 0.0586671
[400]	training's rmse: 0.0475353	valid_1's rmse: 0.0492602
[500]	training's rmse: 0.0447344	valid_1's rmse: 0.0471132
[600]	training's rmse: 0.0435196	valid_1's rmse: 0.0465598
[700]	training's rmse: 0.0426755	valid_1's rmse: 0.0462999
[800]	training's rmse: 0.0419673	valid_1's rmse: 0.0461619
[900]	training's rmse: 0.0413599	valid_1's rmse: 0.0461027
[1000]	training's rmse: 0.0408172	valid_1's rmse: 0.0460891
[1100]	training's rmse: 0.0403146	valid_1's rmse: 0.0461019
Early stopping, best iteration is:
[977]	training's rmse: 0.0409576	valid_1's rmse: 0.046076
folds 1
Training until validation scores don't improve for 200 rounds
[100]	training's rmse: 0.226544	valid_1's rmse: 0.225426
[200]	training's rmse: 0.0971282	valid_1's rmse: 0.0981563
[300]	training's rmse: 0.0573839	valid_1's rmse: 0.0604765
[400]	training's rmse: 0.0468133	valid_1's rmse: 0.0513215
[500]	training's rmse: 0.04392	valid_1's rmse: 0.0493315
[600]	training's rmse: 0.0426995	valid_1's rmse: 0.0488075
[700]	training's rmse: 0.0418527	valid_1's rmse: 0.0485998
[800]	training's rmse: 0.0411682	valid_1's rmse: 0.0485575
[900]	training's rmse: 0.040566	valid_1's rmse: 0.048484
[1000]	training's rmse: 0.0400298	valid_1's rmse: 0.0484444
[1100]	training's rmse: 0.0395374	valid_1's rmse: 0.0484197
[1200]	training's rmse: 0.0390424	valid_1's rmse: 0.0484038
[1300]	training's rmse: 0.0385941	valid_1's rmse: 0.0483951
[1400]	training's rmse: 0.0381847	valid_1's rmse: 0.048402
[1500]	training's rmse: 0.0377891	valid_1's rmse: 0.048371
[1600]	training's rmse: 0.037364	valid_1's rmse: 0.0483954
[1700]	training's rmse: 0.0370085	valid_1's rmse: 0.0483913
Early stopping, best iteration is:
[1502]	training's rmse: 0.0377785	valid_1's rmse: 0.0483691
folds 2
Training until validation scores don't improve for 200 rounds
[100]	training's rmse: 0.227932	valid_1's rmse: 0.229577
[200]	training's rmse: 0.100058	valid_1's rmse: 0.101833
[300]	training's rmse: 0.0584845	valid_1's rmse: 0.060349
[400]	training's rmse: 0.0480128	valid_1's rmse: 0.050103
[500]	training's rmse: 0.0451386	valid_1's rmse: 0.0474865
[600]	training's rmse: 0.0438463	valid_1's rmse: 0.0467042
[700]	training's rmse: 0.0430083	valid_1's rmse: 0.0463218
[800]	training's rmse: 0.0423034	valid_1's rmse: 0.0461414
[900]	training's rmse: 0.0416902	valid_1's rmse: 0.0460446
[1000]	training's rmse: 0.0411211	valid_1's rmse: 0.0460113
[1100]	training's rmse: 0.0406169	valid_1's rmse: 0.0459762
[1200]	training's rmse: 0.0401204	valid_1's rmse: 0.0459549
[1300]	training's rmse: 0.0396321	valid_1's rmse: 0.0459738
[1400]	training's rmse: 0.0392071	valid_1's rmse: 0.0459784
Early stopping, best iteration is:
[1206]	training's rmse: 0.0400926	valid_1's rmse: 0.0459515
folds 3
Training until validation scores don't improve for 200 rounds
[100]	training's rmse: 0.226307	valid_1's rmse: 0.227556
[200]	training's rmse: 0.0974512	valid_1's rmse: 0.098307
[300]	training's rmse: 0.0581506	valid_1's rmse: 0.0590657
[400]	training's rmse: 0.047742	valid_1's rmse: 0.048951
[500]	training's rmse: 0.0448986	valid_1's rmse: 0.0465751
[600]	training's rmse: 0.0436506	valid_1's rmse: 0.0459655
[700]	training's rmse: 0.0427668	valid_1's rmse: 0.0457833
[800]	training's rmse: 0.0421014	valid_1's rmse: 0.0456473
[900]	training's rmse: 0.0414596	valid_1's rmse: 0.0455921
[1000]	training's rmse: 0.0408817	valid_1's rmse: 0.0455654
[1100]	training's rmse: 0.0403698	valid_1's rmse: 0.0455323
[1200]	training's rmse: 0.0398803	valid_1's rmse: 0.0455336
[1300]	training's rmse: 0.0394193	valid_1's rmse: 0.0455275
Early stopping, best iteration is:
[1164]	training's rmse: 0.0400544	valid_1's rmse: 0.0455123
oof_rmse: 0.046490504968166625
oof_mse: 0.0021613670521951254
test_rmse: 0.10498955445882613
test_mse: 0.011022806545462817
oof_mape: [0.04896782]
test_mape: [0.13560733]
verification r2: 0.99351663488233
test r2: 0.9630887068109539
regre ranking shape (27116, 2)
[LightGBM] [Warning] min_data_in_leaf is set=60, min_child_samples=30 will be ignored. Current value: min_data_in_leaf=60
[LightGBM] [Warning] min_data_in_leaf is set=60, min_child_samples=30 will be ignored. Current value: min_data_in_leaf=60
[LightGBM] [Warning] min_data_in_leaf is set=60, min_child_samples=30 will be ignored. Current value: min_data_in_leaf=60
[LightGBM] [Warning] min_data_in_leaf is set=60, min_child_samples=30 will be ignored. Current value: min_data_in_leaf=60
20210919 rov_feature_add_v1 feature table finish
20210918 rov_feature_add_v1 feature table finish
20210917 rov_feature_add_v1 feature table finish
20210916 rov_feature_add_v1 feature table finish
20210915 rov_feature_add_v1 feature table finish
20210914 rov_feature_add_v1 feature table finish
20210913 rov_feature_add_v1 feature table finish
20210912 rov_feature_add_v1 feature table finish
20210911 rov_feature_add_v1 feature table finish
20210910 rov_feature_add_v1 feature table finish
20210909 rov_feature_add_v1 feature table finish
20210908 rov_feature_add_v1 feature table finish
20210907 rov_feature_add_v1 feature table finish
20210906 rov_feature_add_v1 feature table finish
20210905 rov_feature_add_v1 feature table finish
20210904 rov_feature_add_v1 feature table finish
20210903 rov_feature_add_v1 feature table finish
20210902 rov_feature_add_v1 feature table finish
20210901 rov_feature_add_v1 feature table finish
20210831 rov_feature_add_v1 feature table finish
20210830 rov_feature_add_v1 feature table finish
20210829 rov_feature_add_v1 feature table finish
20210828 rov_feature_add_v1 feature table finish
20210827 rov_feature_add_v1 feature table finish
20210826 rov_feature_add_v1 feature table finish
20210825 rov_feature_add_v1 feature table finish
20210824 rov_feature_add_v1 feature table finish
20210823 rov_feature_add_v1 feature table finish
20210822 rov_feature_add_v1 feature table finish
20210821 rov_feature_add_v1 feature table finish
20210925 rov_predict_table_add_v1 feature table finish
stage 1: time cost : 0.07594 sec
stage 2: time cost : 0.07060 sec
stage 3: time cost : 0.08065 sec
stage 4: time cost : 0.08395 sec
stage 1: time cost : 0.00955 sec
stage 2: time cost : 0.00875 sec
stage 3: time cost : 0.00866 sec
stage 4: time cost : 0.00883 sec
151
121
(776799, 121)
151
121
(21060, 121)
0        5.953243
1        6.812345
2        4.634729
3        4.990433
4        3.931826
           ...   
21055    0.000000
21056    0.000000
21057    0.000000
21058    0.000000
21059    0.000000
Name: weighted_retrn_log, Length: 21060, dtype: float64
value feature generate successfully
videoid feature generate successfully
lenth tag_dict: 47609
tag tfidf feature generate successfully
tag dimension: 59393
lenth words_dict: 189467
tag tfidf feature generate successfully
words dimension: 59390
folds 0
Training until validation scores don't improve for 200 rounds
[100]	training's rmse: 0.217296	valid_1's rmse: 0.219055
[200]	training's rmse: 0.0933997	valid_1's rmse: 0.0957921
[300]	training's rmse: 0.054594	valid_1's rmse: 0.0577442
[400]	training's rmse: 0.044312	valid_1's rmse: 0.0479771
[500]	training's rmse: 0.0415086	valid_1's rmse: 0.0457105
[600]	training's rmse: 0.0402481	valid_1's rmse: 0.0450285
[700]	training's rmse: 0.0393805	valid_1's rmse: 0.0447715
[800]	training's rmse: 0.0386728	valid_1's rmse: 0.0446799
[900]	training's rmse: 0.0380495	valid_1's rmse: 0.0446337
[1000]	training's rmse: 0.0374717	valid_1's rmse: 0.0446179
[1100]	training's rmse: 0.0369606	valid_1's rmse: 0.0445955
[1200]	training's rmse: 0.0364684	valid_1's rmse: 0.0445982
[1300]	training's rmse: 0.0359899	valid_1's rmse: 0.0446047
[1400]	training's rmse: 0.0355138	valid_1's rmse: 0.0446262
Early stopping, best iteration is:
[1220]	training's rmse: 0.0363808	valid_1's rmse: 0.0445906
folds 1
Training until validation scores don't improve for 200 rounds
[100]	training's rmse: 0.215789	valid_1's rmse: 0.214513
[200]	training's rmse: 0.0931099	valid_1's rmse: 0.092297
[300]	training's rmse: 0.0546024	valid_1's rmse: 0.0552234
[400]	training's rmse: 0.0443371	valid_1's rmse: 0.0464082
[500]	training's rmse: 0.0414791	valid_1's rmse: 0.0446326
[600]	training's rmse: 0.0402743	valid_1's rmse: 0.0442435
[700]	training's rmse: 0.0394273	valid_1's rmse: 0.0440974
[800]	training's rmse: 0.0387161	valid_1's rmse: 0.0440401
[900]	training's rmse: 0.0380969	valid_1's rmse: 0.044004
[1000]	training's rmse: 0.0375615	valid_1's rmse: 0.0439732
[1100]	training's rmse: 0.0370498	valid_1's rmse: 0.0439087
[1200]	training's rmse: 0.0365759	valid_1's rmse: 0.0438935
[1300]	training's rmse: 0.036118	valid_1's rmse: 0.0439083
Early stopping, best iteration is:
[1172]	training's rmse: 0.036709	valid_1's rmse: 0.0438807
folds 2
Training until validation scores don't improve for 200 rounds
[100]	training's rmse: 0.220769	valid_1's rmse: 0.220882
[200]	training's rmse: 0.0971585	valid_1's rmse: 0.0977065
[300]	training's rmse: 0.0570418	valid_1's rmse: 0.0587242
[400]	training's rmse: 0.04556	valid_1's rmse: 0.0483838
[500]	training's rmse: 0.0421882	valid_1's rmse: 0.0457825
[600]	training's rmse: 0.0408069	valid_1's rmse: 0.0449982
[700]	training's rmse: 0.0398654	valid_1's rmse: 0.0446595
[800]	training's rmse: 0.0391188	valid_1's rmse: 0.0444782
[900]	training's rmse: 0.0384418	valid_1's rmse: 0.0443802
[1000]	training's rmse: 0.0378518	valid_1's rmse: 0.0443594
[1100]	training's rmse: 0.037322	valid_1's rmse: 0.0443377
[1200]	training's rmse: 0.036808	valid_1's rmse: 0.0443101
[1300]	training's rmse: 0.0363635	valid_1's rmse: 0.0442829
[1400]	training's rmse: 0.0359017	valid_1's rmse: 0.0442798
[1500]	training's rmse: 0.0354922	valid_1's rmse: 0.0443043
Early stopping, best iteration is:
[1324]	training's rmse: 0.036253	valid_1's rmse: 0.0442693
folds 3
Training until validation scores don't improve for 200 rounds
[100]	training's rmse: 0.215786	valid_1's rmse: 0.216227
[200]	training's rmse: 0.0932123	valid_1's rmse: 0.094359
[300]	training's rmse: 0.0548723	valid_1's rmse: 0.0562601
[400]	training's rmse: 0.0448026	valid_1's rmse: 0.0462832
[500]	training's rmse: 0.0420321	valid_1's rmse: 0.0437981
[600]	training's rmse: 0.0408233	valid_1's rmse: 0.0429686
[700]	training's rmse: 0.0400402	valid_1's rmse: 0.042586
[800]	training's rmse: 0.0393215	valid_1's rmse: 0.0424025
[900]	training's rmse: 0.0386931	valid_1's rmse: 0.0422996
[1000]	training's rmse: 0.0381022	valid_1's rmse: 0.0422256
[1100]	training's rmse: 0.0375841	valid_1's rmse: 0.0421743
[1200]	training's rmse: 0.0370754	valid_1's rmse: 0.042115
[1300]	training's rmse: 0.0365871	valid_1's rmse: 0.0420674
[1400]	training's rmse: 0.0361483	valid_1's rmse: 0.0420477
[1500]	training's rmse: 0.0356979	valid_1's rmse: 0.0420595
[1600]	training's rmse: 0.0352963	valid_1's rmse: 0.0420646
Early stopping, best iteration is:
[1430]	training's rmse: 0.0360223	valid_1's rmse: 0.042041
oof_rmse: 0.04370656860219149
oof_mse: 0.0019102641389780713
test_rmse: 0.030188856957077185
test_mse: 0.0009113670843748676
oof_mape: [0.04676871]
test_mape: [0.13009724]
verification r2: 0.9937893006007936
test r2: 0.9634331570023774
regre ranking shape (21060, 2)