winlen	winstep	model	loss	accuracy

(array([0, 1]), array([476266, 325691]))
0.025	0.01	bottle3	0.3389156284828169	0.8597792879855353

model_0.025_0.01_bottle3
(array([0, 1]), array([476266, 325691]))
0.025	0.01	bottle5	0.30842042285169746	0.874156742939086

model_0.025_0.01_bottle5
(array([0, 1]), array([476266, 325691]))
0.025	0.01	bottle8	0.2965808613601041	0.8830849803611148

model_0.025_0.01_bottle8
(array([0, 1]), array([476266, 325691]))
0.025	0.01	bottle13	0.28287798926393115	0.889955732901797

model_0.025_0.01_bottle13
(array([0, 1, 2, 3]), array([476266, 125684, 151977,  48030]))
0.025	0.01	multi3	0.48447136703078025	0.8319970072947191

model_0.025_0.01_multi3
(array([0, 1, 2, 3]), array([476266, 125684, 151977,  48030]))
0.025	0.01	multi5	0.43238697158434836	0.8497038468739897

model_0.025_0.01_multi5
(array([0, 1, 2, 3]), array([476266, 125684, 151977,  48030]))
0.025	0.01	multi8	0.4072758802538003	0.8624353139223143

model_0.025_0.01_multi8
(array([0, 1, 2, 3]), array([476266, 125684, 151977,  48030]))
0.025	0.01	multi13	0.3707011521600716	0.868520481326766

model_0.025_0.01_multi13
(array([0, 1]), array([119037,  81431]))
0.1	0.04	bottle3	0.32152209714074387	0.8698992317728829

model_0.1_0.04_bottle3
(array([0, 1]), array([119037,  81431]))
0.1	0.04	bottle5	0.29785478306865665	0.879028235071257

model_0.1_0.04_bottle5
(array([0, 1]), array([119037,  81431]))
0.1	0.04	bottle8	0.31144997012195363	0.8783797266109135

model_0.1_0.04_bottle8
(array([0, 1]), array([119037,  81431]))
0.1	0.04	bottle13	0.28727721201615886	0.8858126309547645

model_0.1_0.04_bottle13
(array([0, 1, 2, 3]), array([119037,  31435,  37996,  12000]))
0.1	0.04	multi3	0.47640502210221436	0.824603412157997

model_0.1_0.04_multi3
(array([0, 1, 2, 3]), array([119037,  31435,  37996,  12000]))
0.1	0.04	multi5	0.44105214603370885	0.8400678439588946

model_0.1_0.04_multi5
(array([0, 1, 2, 3]), array([119037,  31435,  37996,  12000]))
0.1	0.04	multi8	0.3903473072779056	0.8636635737803053

model_0.1_0.04_multi8
(array([0, 1, 2, 3]), array([119037,  31435,  37996,  12000]))
0.1	0.04	multi13	0.3752127004474934	0.8698493464852026

model_0.1_0.04_multi13
(array([0, 1]), array([59493, 40723]))
0.2	0.08	bottle3	0.35470913447088	0.847719788444267

model_0.2_0.08_bottle3
(array([0, 1]), array([59493, 40723]))
0.2	0.08	bottle5	0.32276059763122966	0.870272427901407

model_0.2_0.08_bottle5
(array([0, 1]), array([59493, 40723]))
0.2	0.08	bottle8	0.2949916362783269	0.8849416225925556

model_0.2_0.08_bottle8
(array([0, 1]), array([59493, 40723]))
0.2	0.08	bottle13	0.3005677448865742	0.8803512623490669

model_0.2_0.08_bottle13
(array([0, 1, 2, 3]), array([59493, 15726, 18993,  6004]))
0.2	0.08	multi3	0.4804011737202328	0.8227721784312548

model_0.2_0.08_multi3
(array([0, 1, 2, 3]), array([59493, 15726, 18993,  6004]))
0.2	0.08	multi5	0.4430828566863061	0.8434287995210059

model_0.2_0.08_multi5
(array([0, 1, 2, 3]), array([59493, 15726, 18993,  6004]))
0.2	0.08	multi8	0.39796411239295504	0.8585969464244296

model_0.2_0.08_multi8
(array([0, 1, 2, 3]), array([59493, 15726, 18993,  6004]))
0.2	0.08	multi13	0.391048318939632	0.8592954794930646

model_0.2_0.08_multi13