clarin2sent / deeptagger

lr =  0.002 number_of_relations =  10
model MLP_2_1 :  nchd_dim =  100 ne_dim =  100

('Valid: ', '80.94', 'Valid root: ', '32.52', ' Test all: ', '80.69', 'Test root: ', '32.71', ' Train all: ', '81.35', 'Train root: ', '33.80', '   time: ', 694.1621360778809)
('Valid: ', '81.77', 'Valid root: ', '34.88', ' Test all: ', '81.57', 'Test root: ', '33.62', ' Train all: ', '82.46', 'Train root: ', '37.78', '   time: ', 1367.0440831184387)
('Valid: ', '82.05', 'Valid root: ', '36.42', ' Test all: ', '81.96', 'Test root: ', '36.06', ' Train all: ', '82.83', 'Train root: ', '36.37', '   time: ', 2038.2089231014252)
('Valid: ', '82.64', 'Valid root: ', '36.15', ' Test all: ', '82.52', 'Test root: ', '34.21', ' Train all: ', '84.50', 'Train root: ', '39.30', '   time: ', 2708.9364051818848)
('Valid: ', '82.93', 'Valid root: ', '37.69', ' Test all: ', '82.57', 'Test root: ', '36.38', ' Train all: ', '84.04', 'Train root: ', '38.13', '   time: ', 3377.5660030841827)
('Valid: ', '83.09', 'Valid root: ', '38.69', ' Test all: ', '82.97', 'Test root: ', '37.38', ' Train all: ', '85.32', 'Train root: ', '44.91', '   time: ', 4044.709060192108)
('Valid: ', '83.48', 'Valid root: ', '40.51', ' Test all: ', '83.09', 'Test root: ', '37.24', ' Train all: ', '84.85', 'Train root: ', '45.61', '   time: ', 4711.8197910785675)
('Valid: ', '83.70', 'Valid root: ', '39.69', ' Test all: ', '83.48', 'Test root: ', '37.10', ' Train all: ', '85.81', 'Train root: ', '42.46', '   time: ', 5383.254247188568)
('Valid: ', '83.46', 'Valid root: ', '40.24', ' Test all: ', '83.11', 'Test root: ', '37.42', ' Train all: ', '85.33', 'Train root: ', '43.86', '   time: ', 6060.484612226486)
('Valid: ', '83.50', 'Valid root: ', '36.97', ' Test all: ', '83.28', 'Test root: ', '33.89', ' Train all: ', '85.87', 'Train root: ', '41.75', '   time: ', 6738.443374156952)
('Valid: ', '83.87', 'Valid root: ', '38.06', ' Test all: ', '83.78', 'Test root: ', '36.79', ' Train all: ', '86.45', 'Train root: ', '43.16', '   time: ', 7411.46985411644)
('Valid: ', '83.65', 'Valid root: ', '38.51', ' Test all: ', '83.69', 'Test root: ', '36.29', ' Train all: ', '86.54', 'Train root: ', '45.15', '   time: ', 8084.93486905098)
('Valid: ', '83.91', 'Valid root: ', '38.78', ' Test all: ', '83.84', 'Test root: ', '38.05', ' Train all: ', '87.59', 'Train root: ', '48.89', '   time: ', 8758.386350154877)
('Valid: ', '83.35', 'Valid root: ', '36.78', ' Test all: ', '83.28', 'Test root: ', '36.92', ' Train all: ', '87.29', 'Train root: ', '49.82', '   time: ', 9433.318347215652)
('Valid: ', '83.54', 'Valid root: ', '40.78', ' Test all: ', '83.49', 'Test root: ', '37.87', ' Train all: ', '87.57', 'Train root: ', '52.28', '   time: ', 10102.904543161392)
('Valid: ', '83.93', 'Valid root: ', '37.97', ' Test all: ', '83.91', 'Test root: ', '37.15', ' Train all: ', '88.31', 'Train root: ', '49.71', '   time: ', 10768.449100017548)
('Valid: ', '83.85', 'Valid root: ', '34.33', ' Test all: ', '83.81', 'Test root: ', '35.25', ' Train all: ', '88.21', 'Train root: ', '50.88', '   time: ', 11427.334531068802)
('Valid: ', '83.90', 'Valid root: ', '39.06', ' Test all: ', '83.81', 'Test root: ', '37.38', ' Train all: ', '88.61', 'Train root: ', '52.05', '   time: ', 12086.304541110992)
('Valid: ', '83.76', 'Valid root: ', '35.79', ' Test all: ', '83.87', 'Test root: ', '37.69', ' Train all: ', '89.14', 'Train root: ', '53.10', '   time: ', 12745.68847322464)
('Valid: ', '83.93', 'Valid root: ', '36.78', ' Test all: ', '83.77', 'Test root: ', '36.38', ' Train all: ', '89.52', 'Train root: ', '54.85', '   time: ', 13404.832997083664)
('Valid: ', '83.79', 'Valid root: ', '36.97', ' Test all: ', '83.91', 'Test root: ', '36.06', ' Train all: ', '90.15', 'Train root: ', '54.85', '   time: ', 14063.957324028015)
('Best valid: ', '83.93', ' Test all: ', '83.91', 'Test root: ', '37.15', '   time: ', 14063.957374095917)

lr =  0.002 number_of_relations =  10
model MLP_2_1 :  nchd_dim =  300 ne_dim =  300

('Valid: ', '81.21', 'Valid root: ', '34.60', ' Test all: ', '80.95', 'Test root: ', '34.25', ' Train all: ', '81.66', 'Train root: ', '36.96', '   time: ', 996.2018599510193)
('Valid: ', '81.87', 'Valid root: ', '35.88', ' Test all: ', '81.89', 'Test root: ', '34.07', ' Train all: ', '83.11', 'Train root: ', '40.47', '   time: ', 1963.445277929306)
('Valid: ', '82.34', 'Valid root: ', '37.42', ' Test all: ', '82.20', 'Test root: ', '35.97', ' Train all: ', '83.14', 'Train root: ', '37.19', '   time: ', 2930.071177959442)
('Valid: ', '82.75', 'Valid root: ', '38.51', ' Test all: ', '82.61', 'Test root: ', '34.84', ' Train all: ', '84.90', 'Train root: ', '42.11', '   time: ', 3896.6491827964783)
('Valid: ', '83.20', 'Valid root: ', '38.51', ' Test all: ', '82.72', 'Test root: ', '36.33', ' Train all: ', '84.72', 'Train root: ', '39.06', '   time: ', 4863.202253818512)
('Valid: ', '83.09', 'Valid root: ', '37.51', ' Test all: ', '83.12', 'Test root: ', '37.29', ' Train all: ', '85.67', 'Train root: ', '45.85', '   time: ', 5829.131693840027)
('Valid: ', '83.45', 'Valid root: ', '39.15', ' Test all: ', '83.07', 'Test root: ', '37.19', ' Train all: ', '85.64', 'Train root: ', '47.37', '   time: ', 6792.115895032883)
('Valid: ', '83.57', 'Valid root: ', '38.96', ' Test all: ', '83.34', 'Test root: ', '36.56', ' Train all: ', '86.48', 'Train root: ', '44.68', '   time: ', 7755.166389942169)
('Valid: ', '83.33', 'Valid root: ', '38.87', ' Test all: ', '82.97', 'Test root: ', '36.47', ' Train all: ', '86.21', 'Train root: ', '47.25', '   time: ', 8718.30408501625)
('Valid: ', '83.53', 'Valid root: ', '37.06', ' Test all: ', '83.42', 'Test root: ', '34.98', ' Train all: ', '86.90', 'Train root: ', '43.63', '   time: ', 9686.083489894867)
('Valid: ', '83.67', 'Valid root: ', '36.51', ' Test all: ', '83.63', 'Test root: ', '35.70', ' Train all: ', '87.47', 'Train root: ', '49.47', '   time: ', 10649.54754281044)
('Valid: ', '83.60', 'Valid root: ', '38.15', ' Test all: ', '83.48', 'Test root: ', '35.88', ' Train all: ', '87.68', 'Train root: ', '49.71', '   time: ', 11612.906508922577)
('Valid: ', '83.73', 'Valid root: ', '37.42', ' Test all: ', '83.65', 'Test root: ', '36.61', ' Train all: ', '88.67', 'Train root: ', '51.70', '   time: ', 12577.347810029984)
('Valid: ', '83.15', 'Valid root: ', '35.24', ' Test all: ', '83.14', 'Test root: ', '36.43', ' Train all: ', '88.41', 'Train root: ', '53.68', '   time: ', 13540.648028850555)
('Valid: ', '83.39', 'Valid root: ', '39.51', ' Test all: ', '83.36', 'Test root: ', '37.42', ' Train all: ', '88.97', 'Train root: ', '56.14', '   time: ', 14503.961890935898)
('Valid: ', '83.51', 'Valid root: ', '36.88', ' Test all: ', '83.61', 'Test root: ', '35.57', ' Train all: ', '89.87', 'Train root: ', '54.85', '   time: ', 15467.27589392662)
('Valid: ', '83.73', 'Valid root: ', '33.97', ' Test all: ', '83.48', 'Test root: ', '34.43', ' Train all: ', '90.01', 'Train root: ', '56.84', '   time: ', 16430.695183992386)
('Valid: ', '83.71', 'Valid root: ', '37.60', ' Test all: ', '83.50', 'Test root: ', '36.06', ' Train all: ', '90.77', 'Train root: ', '60.58', '   time: ', 17394.078981876373)
('Valid: ', '82.83', 'Valid root: ', '33.24', ' Test all: ', '83.17', 'Test root: ', '36.74', ' Train all: ', '90.80', 'Train root: ', '57.66', '   time: ', 18357.310384988785)
('Valid: ', '83.56', 'Valid root: ', '36.24', ' Test all: ', '83.53', 'Test root: ', '35.75', ' Train all: ', '91.62', 'Train root: ', '62.57', '   time: ', 19320.686059951782)
('Valid: ', '83.07', 'Valid root: ', '36.24', ' Test all: ', '83.19', 'Test root: ', '35.25', ' Train all: ', '91.95', 'Train root: ', '63.04', '   time: ', 20283.9747300148)
('Valid: ', '83.62', 'Valid root: ', '37.78', ' Test all: ', '83.58', 'Test root: ', '36.11', ' Train all: ', '92.64', 'Train root: ', '65.73', '   time: ', 21248.616806030273)
('Best valid: ', '83.73', ' Test all: ', '83.48', 'Test root: ', '34.43', '   time: ', 21248.616869926453)

lr =  0.002 number_of_relations =  20
model MLP_2_1 :  nchd_dim =  100 ne_dim =  100

('Valid: ', '80.90', 'Valid root: ', '32.33', ' Test all: ', '80.79', 'Test root: ', '32.44', ' Train all: ', '81.47', 'Train root: ', '34.27', '   time: ', 650.6330649852753)
('Valid: ', '81.71', 'Valid root: ', '33.79', ' Test all: ', '81.55', 'Test root: ', '32.85', ' Train all: ', '82.46', 'Train root: ', '36.49', '   time: ', 1301.0441279411316)
('Valid: ', '82.03', 'Valid root: ', '35.24', ' Test all: ', '81.97', 'Test root: ', '35.88', ' Train all: ', '82.94', 'Train root: ', '36.61', '   time: ', 1951.6336629390717)
('Valid: ', '82.48', 'Valid root: ', '36.24', ' Test all: ', '82.49', 'Test root: ', '34.84', ' Train all: ', '84.61', 'Train root: ', '41.05', '   time: ', 2602.325767993927)
('Valid: ', '83.02', 'Valid root: ', '37.69', ' Test all: ', '82.70', 'Test root: ', '35.97', ' Train all: ', '84.35', 'Train root: ', '38.25', '   time: ', 3253.050611972809)
('Valid: ', '82.90', 'Valid root: ', '37.78', ' Test all: ', '82.91', 'Test root: ', '36.74', ' Train all: ', '85.40', 'Train root: ', '45.38', '   time: ', 3903.1578629016876)
('Valid: ', '83.50', 'Valid root: ', '39.33', ' Test all: ', '83.17', 'Test root: ', '37.15', ' Train all: ', '85.04', 'Train root: ', '44.91', '   time: ', 4551.963771820068)
('Valid: ', '83.59', 'Valid root: ', '38.24', ' Test all: ', '83.32', 'Test root: ', '36.38', ' Train all: ', '85.80', 'Train root: ', '42.22', '   time: ', 5202.451989889145)
('Valid: ', '83.11', 'Valid root: ', '38.78', ' Test all: ', '82.93', 'Test root: ', '37.78', ' Train all: ', '85.39', 'Train root: ', '43.86', '   time: ', 5849.917150020599)
('Valid: ', '83.44', 'Valid root: ', '37.15', ' Test all: ', '83.33', 'Test root: ', '34.03', ' Train all: ', '86.16', 'Train root: ', '43.86', '   time: ', 6497.305151939392)
('Valid: ', '83.75', 'Valid root: ', '36.42', ' Test all: ', '83.65', 'Test root: ', '35.16', ' Train all: ', '86.81', 'Train root: ', '44.68', '   time: ', 7170.068682909012)
('Valid: ', '83.60', 'Valid root: ', '38.15', ' Test all: ', '83.60', 'Test root: ', '35.70', ' Train all: ', '86.58', 'Train root: ', '45.61', '   time: ', 7879.155040979385)
('Valid: ', '83.85', 'Valid root: ', '38.24', ' Test all: ', '83.74', 'Test root: ', '38.42', ' Train all: ', '87.90', 'Train root: ', '50.88', '   time: ', 8582.118552923203)
('Valid: ', '83.35', 'Valid root: ', '36.06', ' Test all: ', '83.43', 'Test root: ', '36.38', ' Train all: ', '87.87', 'Train root: ', '51.46', '   time: ', 9282.297809839249)
('Valid: ', '83.41', 'Valid root: ', '39.06', ' Test all: ', '83.51', 'Test root: ', '38.28', ' Train all: ', '87.98', 'Train root: ', '52.40', '   time: ', 9986.745368003845)
('Valid: ', '83.60', 'Valid root: ', '36.15', ' Test all: ', '83.70', 'Test root: ', '35.02', ' Train all: ', '89.04', 'Train root: ', '50.64', '   time: ', 10688.230065822601)
('Valid: ', '83.69', 'Valid root: ', '34.97', ' Test all: ', '83.71', 'Test root: ', '34.43', ' Train all: ', '89.00', 'Train root: ', '53.57', '   time: ', 11384.62016582489)
('Valid: ', '83.56', 'Valid root: ', '36.88', ' Test all: ', '83.80', 'Test root: ', '36.92', ' Train all: ', '89.26', 'Train root: ', '55.79', '   time: ', 12078.017078876495)
('Best valid: ', '83.85', ' Test all: ', '83.74', 'Test root: ', '38.42', '   time: ', 12078.017130851746)


lr =  0.002 number_of_relations =  5
model MLP_2_2 :  nchd_dim =  50 ne_dim =  50 nh2 = 50

('Valid: ', '80.23', 'Valid root: ', '30.79', ' Test all: ', '80.31', 'Test root: ', '32.85', ' Train all: ', '80.96', 'Train root: ', '34.74', '   time: ', 619.501345872879)
('Valid: ', '81.71', 'Valid root: ', '31.24', ' Test all: ', '81.50', 'Test root: ', '28.60', ' Train all: ', '82.35', 'Train root: ', '33.10', '   time: ', 1243.7717249393463)
('Valid: ', '82.62', 'Valid root: ', '37.33', ' Test all: ', '82.45', 'Test root: ', '37.92', ' Train all: ', '83.39', 'Train root: ', '37.66', '   time: ', 1861.3532860279083)
('Valid: ', '83.78', 'Valid root: ', '36.33', ' Test all: ', '83.53', 'Test root: ', '34.57', ' Train all: ', '85.06', 'Train root: ', '38.83', '   time: ', 2480.895786046982)
('Valid: ', '84.22', 'Valid root: ', '40.51', ' Test all: ', '83.72', 'Test root: ', '38.33', ' Train all: ', '85.02', 'Train root: ', '41.40', '   time: ', 3096.1500358581543)
('Valid: ', '84.70', 'Valid root: ', '40.05', ' Test all: ', '84.25', 'Test root: ', '37.47', ' Train all: ', '86.57', 'Train root: ', '43.16', '   time: ', 3708.891681909561)
('Valid: ', '85.12', 'Valid root: ', '41.69', ' Test all: ', '84.70', 'Test root: ', '38.82', ' Train all: ', '86.23', 'Train root: ', '43.51', '   time: ', 4332.522243976593)
('Valid: ', '85.39', 'Valid root: ', '41.60', ' Test all: ', '84.85', 'Test root: ', '40.18', ' Train all: ', '86.57', 'Train root: ', '42.81', '   time: ', 4950.690151929855)
('Valid: ', '85.32', 'Valid root: ', '40.51', ' Test all: ', '84.90', 'Test root: ', '38.60', ' Train all: ', '86.77', 'Train root: ', '42.11', '   time: ', 5592.100620031357)
('Valid: ', '85.46', 'Valid root: ', '39.42', ' Test all: ', '85.16', 'Test root: ', '37.15', ' Train all: ', '86.93', 'Train root: ', '39.53', '   time: ', 6202.998632907867)
('Valid: ', '85.66', 'Valid root: ', '40.78', ' Test all: ', '85.30', 'Test root: ', '37.87', ' Train all: ', '87.12', 'Train root: ', '42.34', '   time: ', 6818.481505870819)
('Valid: ', '85.68', 'Valid root: ', '40.05', ' Test all: ', '85.23', 'Test root: ', '39.10', ' Train all: ', '87.39', 'Train root: ', '44.91', '   time: ', 7434.671463012695)
('Valid: ', '85.72', 'Valid root: ', '43.60', ' Test all: ', '85.20', 'Test root: ', '39.59', ' Train all: ', '88.05', 'Train root: ', '45.26', '   time: ', 8047.896941900253)
('Valid: ', '85.87', 'Valid root: ', '42.14', ' Test all: ', '85.21', 'Test root: ', '38.82', ' Train all: ', '88.07', 'Train root: ', '48.30', '   time: ', 8658.892245054245)
('Valid: ', '85.34', 'Valid root: ', '42.23', ' Test all: ', '84.74', 'Test root: ', '40.36', ' Train all: ', '88.02', 'Train root: ', '47.72', '   time: ', 9268.59084701538)
('Valid: ', '85.99', 'Valid root: ', '41.87', ' Test all: ', '85.39', 'Test root: ', '38.14', ' Train all: ', '88.64', 'Train root: ', '47.84', '   time: ', 9878.38220500946)
('Valid: ', '85.86', 'Valid root: ', '37.24', ' Test all: ', '85.34', 'Test root: ', '35.43', ' Train all: ', '88.02', 'Train root: ', '43.39', '   time: ', 10493.703199863434)
('Valid: ', '85.97', 'Valid root: ', '42.87', ' Test all: ', '85.29', 'Test root: ', '38.24', ' Train all: ', '88.41', 'Train root: ', '47.25', '   time: ', 11115.244982004166)
('Valid: ', '85.56', 'Valid root: ', '39.51', ' Test all: ', '85.29', 'Test root: ', '38.73', ' Train all: ', '88.91', 'Train root: ', '48.65', '   time: ', 11729.459635019302)
('Valid: ', '85.84', 'Valid root: ', '41.69', ' Test all: ', '85.36', 'Test root: ', '38.05', ' Train all: ', '88.97', 'Train root: ', '48.77', '   time: ', 12343.131296873093)
('Valid: ', '85.89', 'Valid root: ', '40.42', ' Test all: ', '85.43', 'Test root: ', '37.42', ' Train all: ', '89.15', 'Train root: ', '48.77', '   time: ', 12956.884922981262)
('Best valid: ', '85.99', ' Test all: ', '85.39', 'Test root: ', '38.14', '   time: ', 12956.884973049164)

lr =  0.002 number_of_relations =  5
model MLP_2_2 :  nchd_dim =  100 ne_dim =  100 nh2 = 100

('Valid: ', '80.88', 'Valid root: ', '34.15', ' Test all: ', '80.47', 'Test root: ', '33.08', ' Train all: ', '81.24', 'Train root: ', '33.22', '   time: ', 641.5466120243073)
('Valid: ', '82.03', 'Valid root: ', '37.87', ' Test all: ', '81.82', 'Test root: ', '34.48', ' Train all: ', '82.69', 'Train root: ', '39.06', '   time: ', 1280.8929619789124)
('Valid: ', '83.17', 'Valid root: ', '38.96', ' Test all: ', '82.87', 'Test root: ', '38.01', ' Train all: ', '83.94', 'Train root: ', '39.18', '   time: ', 1922.1420369148254)
('Valid: ', '83.89', 'Valid root: ', '38.15', ' Test all: ', '83.59', 'Test root: ', '36.20', ' Train all: ', '85.22', 'Train root: ', '40.35', '   time: ', 2563.0579409599304)
('Valid: ', '84.51', 'Valid root: ', '41.60', ' Test all: ', '84.04', 'Test root: ', '39.28', ' Train all: ', '85.50', 'Train root: ', '41.64', '   time: ', 3204.312206029892)
('Valid: ', '84.74', 'Valid root: ', '41.42', ' Test all: ', '84.36', 'Test root: ', '38.60', ' Train all: ', '86.58', 'Train root: ', '44.80', '   time: ', 3843.5399210453033)
('Valid: ', '85.31', 'Valid root: ', '42.96', ' Test all: ', '84.85', 'Test root: ', '40.54', ' Train all: ', '86.64', 'Train root: ', '46.08', '   time: ', 4485.581315040588)
('Valid: ', '85.57', 'Valid root: ', '43.05', ' Test all: ', '84.97', 'Test root: ', '40.77', ' Train all: ', '87.02', 'Train root: ', '44.09', '   time: ', 5126.782865047455)
('Valid: ', '85.59', 'Valid root: ', '41.42', ' Test all: ', '85.00', 'Test root: ', '39.91', ' Train all: ', '86.89', 'Train root: ', '41.87', '   time: ', 5768.172475099564)
('Valid: ', '85.64', 'Valid root: ', '40.69', ' Test all: ', '85.24', 'Test root: ', '38.28', ' Train all: ', '87.17', 'Train root: ', '42.22', '   time: ', 6411.1427710056305)
('Valid: ', '85.68', 'Valid root: ', '40.15', ' Test all: ', '85.28', 'Test root: ', '37.29', ' Train all: ', '87.38', 'Train root: ', '44.56', '   time: ', 7052.718267917633)
('Valid: ', '85.67', 'Valid root: ', '41.51', ' Test all: ', '85.20', 'Test root: ', '38.55', ' Train all: ', '87.71', 'Train root: ', '47.25', '   time: ', 7694.1051280498505)
('Valid: ', '85.82', 'Valid root: ', '42.87', ' Test all: ', '85.33', 'Test root: ', '40.50', ' Train all: ', '88.34', 'Train root: ', '45.61', '   time: ', 8335.624568939209)
('Valid: ', '85.62', 'Valid root: ', '42.14', ' Test all: ', '85.24', 'Test root: ', '39.46', ' Train all: ', '88.29', 'Train root: ', '49.01', '   time: ', 8977.624116897583)
('Valid: ', '85.33', 'Valid root: ', '43.23', ' Test all: ', '84.92', 'Test root: ', '40.95', ' Train all: ', '88.22', 'Train root: ', '49.59', '   time: ', 9622.630855083466)
('Valid: ', '85.95', 'Valid root: ', '42.69', ' Test all: ', '85.33', 'Test root: ', '38.05', ' Train all: ', '88.93', 'Train root: ', '48.77', '   time: ', 10264.303379058838)
('Valid: ', '85.97', 'Valid root: ', '41.05', ' Test all: ', '85.45', 'Test root: ', '36.83', ' Train all: ', '88.40', 'Train root: ', '45.73', '   time: ', 10906.82495689392)
('Valid: ', '85.87', 'Valid root: ', '42.23', ' Test all: ', '85.22', 'Test root: ', '39.73', ' Train all: ', '88.83', 'Train root: ', '48.65', '   time: ', 11548.476881027222)
('Valid: ', '85.32', 'Valid root: ', '38.69', ' Test all: ', '85.33', 'Test root: ', '38.87', ' Train all: ', '89.01', 'Train root: ', '49.94', '   time: ', 12190.40132188797)
('Valid: ', '85.80', 'Valid root: ', '42.51', ' Test all: ', '85.41', 'Test root: ', '39.55', ' Train all: ', '89.52', 'Train root: ', '51.93', '   time: ', 12831.910468101501)
('Valid: ', '85.73', 'Valid root: ', '41.87', ' Test all: ', '85.25', 'Test root: ', '38.51', ' Train all: ', '89.78', 'Train root: ', '53.33', '   time: ', 13473.217606067657)
('Valid: ', '85.84', 'Valid root: ', '41.96', ' Test all: ', '85.34', 'Test root: ', '39.82', ' Train all: ', '90.24', 'Train root: ', '52.05', '   time: ', 14114.582712888718)
('Best valid: ', '85.97', ' Test all: ', '85.45', 'Test root: ', '36.83', '   time: ', 14114.582765102386)

lr =  0.002 number_of_relations =  10
model MLP_2_2 :  nchd_dim =  50 ne_dim =  50 nh2 = 50

('Valid: ', '80.34', 'Valid root: ', '30.06', ' Test all: ', '80.43', 'Test root: ', '32.99', ' Train all: ', '80.97', 'Train root: ', '35.56', '   time: ', 632.2674658298492)
('Valid: ', '81.45', 'Valid root: ', '29.97', ' Test all: ', '81.31', 'Test root: ', '28.46', ' Train all: ', '82.33', 'Train root: ', '31.93', '   time: ', 1262.5781049728394)
('Valid: ', '82.40', 'Valid root: ', '36.78', ' Test all: ', '82.22', 'Test root: ', '37.19', ' Train all: ', '83.20', 'Train root: ', '37.66', '   time: ', 1895.6239500045776)
('Valid: ', '83.54', 'Valid root: ', '36.06', ' Test all: ', '83.52', 'Test root: ', '35.84', ' Train all: ', '85.09', 'Train root: ', '40.35', '   time: ', 2526.945554971695)
('Valid: ', '84.07', 'Valid root: ', '39.69', ' Test all: ', '83.66', 'Test root: ', '38.82', ' Train all: ', '85.07', 'Train root: ', '41.05', '   time: ', 3158.225874900818)
('Valid: ', '84.66', 'Valid root: ', '42.14', ' Test all: ', '84.25', 'Test root: ', '38.96', ' Train all: ', '86.38', 'Train root: ', '43.27', '   time: ', 3789.2723088264465)
('Valid: ', '84.98', 'Valid root: ', '41.24', ' Test all: ', '84.59', 'Test root: ', '38.28', ' Train all: ', '86.07', 'Train root: ', '41.29', '   time: ', 4419.259985923767)
('Valid: ', '85.28', 'Valid root: ', '41.78', ' Test all: ', '84.68', 'Test root: ', '39.50', ' Train all: ', '86.59', 'Train root: ', '40.70', '   time: ', 5048.775353908539)
('Valid: ', '85.20', 'Valid root: ', '42.51', ' Test all: ', '84.85', 'Test root: ', '39.05', ' Train all: ', '86.52', 'Train root: ', '41.99', '   time: ', 5678.01355099678)
('Valid: ', '85.14', 'Valid root: ', '40.05', ' Test all: ', '84.81', 'Test root: ', '34.89', ' Train all: ', '86.50', 'Train root: ', '37.89', '   time: ', 6307.179516792297)
('Valid: ', '85.48', 'Valid root: ', '41.69', ' Test all: ', '85.25', 'Test root: ', '37.51', ' Train all: ', '87.14', 'Train root: ', '43.51', '   time: ', 6936.483620882034)
('Valid: ', '85.51', 'Valid root: ', '41.78', ' Test all: ', '85.15', 'Test root: ', '38.19', ' Train all: ', '87.29', 'Train root: ', '45.03', '   time: ', 7561.87470293045)
('Valid: ', '85.59', 'Valid root: ', '43.05', ' Test all: ', '85.13', 'Test root: ', '39.55', ' Train all: ', '88.02', 'Train root: ', '44.44', '   time: ', 8189.221896886826)
('Valid: ', '85.40', 'Valid root: ', '40.60', ' Test all: ', '85.03', 'Test root: ', '39.86', ' Train all: ', '87.80', 'Train root: ', '46.90', '   time: ', 8882.862586021423)
('Valid: ', '85.21', 'Valid root: ', '42.33', ' Test all: ', '84.34', 'Test root: ', '39.28', ' Train all: ', '88.00', 'Train root: ', '46.55', '   time: ', 9532.975445985794)
('Valid: ', '85.70', 'Valid root: ', '42.05', ' Test all: ', '85.24', 'Test root: ', '38.60', ' Train all: ', '88.61', 'Train root: ', '46.43', '   time: ', 10183.149880886078)
('Valid: ', '85.58', 'Valid root: ', '36.60', ' Test all: ', '85.26', 'Test root: ', '34.21', ' Train all: ', '87.97', 'Train root: ', '44.33', '   time: ', 10825.000183820724)
('Valid: ', '85.86', 'Valid root: ', '41.69', ' Test all: ', '85.45', 'Test root: ', '38.96', ' Train all: ', '88.44', 'Train root: ', '46.08', '   time: ', 11482.602150917053)
('Valid: ', '85.03', 'Valid root: ', '38.24', ' Test all: ', '84.86', 'Test root: ', '37.87', ' Train all: ', '88.54', 'Train root: ', '44.80', '   time: ', 12120.705603837967)
('Valid: ', '85.77', 'Valid root: ', '41.60', ' Test all: ', '84.93', 'Test root: ', '37.56', ' Train all: ', '89.04', 'Train root: ', '49.94', '   time: ', 12754.380872011185)
('Valid: ', '85.85', 'Valid root: ', '41.24', ' Test all: ', '85.21', 'Test root: ', '37.24', ' Train all: ', '89.36', 'Train root: ', '48.19', '   time: ', 13399.70358800888)
('Valid: ', '85.62', 'Valid root: ', '40.69', ' Test all: ', '84.99', 'Test root: ', '38.64', ' Train all: ', '89.78', 'Train root: ', '50.53', '   time: ', 14029.689164876938)
('Valid: ', '85.56', 'Valid root: ', '40.78', ' Test all: ', '84.85', 'Test root: ', '40.23', ' Train all: ', '90.04', 'Train root: ', '50.06', '   time: ', 14666.525396823883)
('Best valid: ', '85.86', ' Test all: ', '85.45', 'Test root: ', '38.96', '   time: ', 14666.525434017181)

lr =  0.002 number_of_relations =  10
model MLP_2_2 :  nchd_dim =  100 ne_dim =  100 nh2 = 100

('Valid: ', '80.84', 'Valid root: ', '32.52', ' Test all: ', '80.63', 'Test root: ', '33.03', ' Train all: ', '81.29', 'Train root: ', '33.68', '   time: ', 683.9910709857941)
('Valid: ', '81.79', 'Valid root: ', '34.33', ' Test all: ', '81.66', 'Test root: ', '31.81', ' Train all: ', '82.74', 'Train root: ', '37.66', '   time: ', 1349.2818939685822)
('Valid: ', '82.89', 'Valid root: ', '37.97', ' Test all: ', '82.72', 'Test root: ', '36.83', ' Train all: ', '83.87', 'Train root: ', '38.60', '   time: ', 2017.0804870128632)
('Valid: ', '83.76', 'Valid root: ', '37.06', ' Test all: ', '83.65', 'Test root: ', '36.33', ' Train all: ', '85.38', 'Train root: ', '41.64', '   time: ', 2696.337615966797)
('Valid: ', '84.45', 'Valid root: ', '41.33', ' Test all: ', '83.96', 'Test root: ', '39.23', ' Train all: ', '85.42', 'Train root: ', '41.75', '   time: ', 3371.4485919475555)
('Valid: ', '84.83', 'Valid root: ', '42.14', ' Test all: ', '84.36', 'Test root: ', '38.28', ' Train all: ', '86.68', 'Train root: ', '44.91', '   time: ', 4037.039141893387)
('Valid: ', '85.21', 'Valid root: ', '42.87', ' Test all: ', '84.77', 'Test root: ', '39.86', ' Train all: ', '86.57', 'Train root: ', '46.43', '   time: ', 4692.226758956909)
('Valid: ', '85.33', 'Valid root: ', '43.23', ' Test all: ', '84.89', 'Test root: ', '40.54', ' Train all: ', '86.87', 'Train root: ', '42.46', '   time: ', 5355.899470806122)
('Valid: ', '85.48', 'Valid root: ', '41.51', ' Test all: ', '85.07', 'Test root: ', '40.09', ' Train all: ', '86.98', 'Train root: ', '43.86', '   time: ', 6020.774860858917)
('Valid: ', '85.48', 'Valid root: ', '40.78', ' Test all: ', '85.21', 'Test root: ', '38.33', ' Train all: ', '87.40', 'Train root: ', '42.92', '   time: ', 6694.7092888355255)
('Valid: ', '85.71', 'Valid root: ', '41.42', ' Test all: ', '85.29', 'Test root: ', '38.73', ' Train all: ', '87.47', 'Train root: ', '45.03', '   time: ', 7404.035621881485)
('Valid: ', '85.60', 'Valid root: ', '41.96', ' Test all: ', '85.27', 'Test root: ', '40.81', ' Train all: ', '87.81', 'Train root: ', '48.07', '   time: ', 8103.766199827194)
('Valid: ', '85.64', 'Valid root: ', '41.78', ' Test all: ', '85.28', 'Test root: ', '40.14', ' Train all: ', '88.38', 'Train root: ', '46.08', '   time: ', 8768.173238992691)
('Valid: ', '85.78', 'Valid root: ', '41.87', ' Test all: ', '85.25', 'Test root: ', '39.91', ' Train all: ', '88.50', 'Train root: ', '49.71', '   time: ', 9436.874769926071)
('Valid: ', '85.22', 'Valid root: ', '42.05', ' Test all: ', '84.84', 'Test root: ', '41.00', ' Train all: ', '88.02', 'Train root: ', '48.89', '   time: ', 10104.806318998337)
('Valid: ', '85.78', 'Valid root: ', '40.69', ' Test all: ', '85.46', 'Test root: ', '39.77', ' Train all: ', '89.07', 'Train root: ', '49.12', '   time: ', 10763.19808292389)
('Valid: ', '85.71', 'Valid root: ', '38.06', ' Test all: ', '85.40', 'Test root: ', '36.70', ' Train all: ', '88.53', 'Train root: ', '47.13', '   time: ', 11420.610905885696)
('Valid: ', '85.82', 'Valid root: ', '40.60', ' Test all: ', '85.22', 'Test root: ', '38.60', ' Train all: ', '89.09', 'Train root: ', '48.89', '   time: ', 12080.21979188919)
('Valid: ', '84.97', 'Valid root: ', '36.33', ' Test all: ', '85.10', 'Test root: ', '39.86', ' Train all: ', '88.94', 'Train root: ', '49.24', '   time: ', 12736.204659938812)
('Valid: ', '85.85', 'Valid root: ', '41.14', ' Test all: ', '85.36', 'Test root: ', '39.32', ' Train all: ', '89.60', 'Train root: ', '52.40', '   time: ', 13392.057343006134)
('Valid: ', '85.55', 'Valid root: ', '40.24', ' Test all: ', '85.27', 'Test root: ', '39.37', ' Train all: ', '90.07', 'Train root: ', '54.04', '   time: ', 14055.33888578415)
('Valid: ', '85.55', 'Valid root: ', '42.78', ' Test all: ', '85.22', 'Test root: ', '39.91', ' Train all: ', '90.36', 'Train root: ', '54.27', '   time: ', 14718.974306821823)
('Valid: ', '85.59', 'Valid root: ', '42.42', ' Test all: ', '85.24', 'Test root: ', '41.40', ' Train all: ', '90.77', 'Train root: ', '54.39', '   time: ', 15391.908160924911)
('Valid: ', '85.46', 'Valid root: ', '39.51', ' Test all: ', '85.32', 'Test root: ', '39.19', ' Train all: ', '90.70', 'Train root: ', '56.37', '   time: ', 16064.247756958008)
('Valid: ', '85.20', 'Valid root: ', '39.60', ' Test all: ', '85.22', 'Test root: ', '40.68', ' Train all: ', '90.57', 'Train root: ', '55.67', '   time: ', 16721.87249994278)
('Best valid: ', '85.85', ' Test all: ', '85.36', 'Test root: ', '39.32', '   time: ', 16721.872552871704)


lr =  0.002 number_of_relations =  5
model MLP_2_2 :  nchd_dim =  200 ne_dim =  200 nh2 = 100

('Valid: ', '81.18', 'Valid root: ', '35.88', ' Test all: ', '80.84', 'Test root: ', '34.62', ' Train all: ', '81.63', 'Train root: ', '37.31', '   time: ', 702.7262439727783)
('Valid: ', '82.55', 'Valid root: ', '38.60', ' Test all: ', '82.39', 'Test root: ', '36.29', ' Train all: ', '83.47', 'Train root: ', '42.81', '   time: ', 1403.9441678524017)
('Valid: ', '83.69', 'Valid root: ', '40.51', ' Test all: ', '83.11', 'Test root: ', '38.64', ' Train all: ', '84.29', 'Train root: ', '40.00', '   time: ', 2100.271680831909)
('Valid: ', '84.18', 'Valid root: ', '39.96', ' Test all: ', '83.79', 'Test root: ', '36.79', ' Train all: ', '85.57', 'Train root: ', '41.29', '   time: ', 2807.2550990581512)
('Valid: ', '84.69', 'Valid root: ', '41.69', ' Test all: ', '83.97', 'Test root: ', '38.78', ' Train all: ', '85.76', 'Train root: ', '42.22', '   time: ', 3509.8950419425964)
('Valid: ', '85.04', 'Valid root: ', '42.78', ' Test all: ', '84.32', 'Test root: ', '39.46', ' Train all: ', '86.84', 'Train root: ', '46.20', '   time: ', 4209.323768854141)
('Valid: ', '85.32', 'Valid root: ', '42.87', ' Test all: ', '84.99', 'Test root: ', '40.54', ' Train all: ', '86.72', 'Train root: ', '45.85', '   time: ', 4924.798982858658)
('Valid: ', '85.55', 'Valid root: ', '44.14', ' Test all: ', '84.94', 'Test root: ', '42.31', ' Train all: ', '87.09', 'Train root: ', '44.09', '   time: ', 5638.09903883934)
('Valid: ', '85.66', 'Valid root: ', '43.23', ' Test all: ', '85.01', 'Test root: ', '40.36', ' Train all: ', '87.38', 'Train root: ', '45.85', '   time: ', 6339.071812868118)
('Valid: ', '85.72', 'Valid root: ', '42.69', ' Test all: ', '85.18', 'Test root: ', '37.69', ' Train all: ', '87.46', 'Train root: ', '43.27', '   time: ', 7043.175123929977)
('Valid: ', '85.79', 'Valid root: ', '41.14', ' Test all: ', '85.35', 'Test root: ', '38.87', ' Train all: ', '87.49', 'Train root: ', '44.56', '   time: ', 7741.885625839233)
('Valid: ', '85.72', 'Valid root: ', '43.05', ' Test all: ', '85.23', 'Test root: ', '38.19', ' Train all: ', '87.92', 'Train root: ', '47.95', '   time: ', 8449.016423940659)
('Valid: ', '85.69', 'Valid root: ', '42.60', ' Test all: ', '85.18', 'Test root: ', '39.82', ' Train all: ', '88.73', 'Train root: ', '46.43', '   time: ', 9155.778992891312)
('Valid: ', '85.76', 'Valid root: ', '42.42', ' Test all: ', '85.27', 'Test root: ', '38.55', ' Train all: ', '88.69', 'Train root: ', '50.64', '   time: ', 9858.602687835693)
('Valid: ', '85.59', 'Valid root: ', '44.41', ' Test all: ', '85.01', 'Test root: ', '40.23', ' Train all: ', '88.64', 'Train root: ', '49.71', '   time: ', 10561.391222953796)
('Valid: ', '85.91', 'Valid root: ', '45.23', ' Test all: ', '85.37', 'Test root: ', '40.27', ' Train all: ', '89.14', 'Train root: ', '50.53', '   time: ', 11263.147186994553)
('Valid: ', '85.97', 'Valid root: ', '39.51', ' Test all: ', '85.19', 'Test root: ', '35.07', ' Train all: ', '88.80', 'Train root: ', '47.13', '   time: ', 11966.210083961487)
('Valid: ', '85.90', 'Valid root: ', '42.51', ' Test all: ', '85.38', 'Test root: ', '40.63', ' Train all: ', '89.45', 'Train root: ', '50.06', '   time: ', 12668.672405958176)
('Valid: ', '85.17', 'Valid root: ', '39.15', ' Test all: ', '85.21', 'Test root: ', '41.04', ' Train all: ', '89.89', 'Train root: ', '51.93', '   time: ', 13375.51733803749)
('Valid: ', '85.86', 'Valid root: ', '42.69', ' Test all: ', '85.20', 'Test root: ', '38.37', ' Train all: ', '89.98', 'Train root: ', '52.51', '   time: ', 14080.268343925476)
('Valid: ', '85.75', 'Valid root: ', '43.23', ' Test all: ', '85.17', 'Test root: ', '38.87', ' Train all: ', '90.64', 'Train root: ', '54.74', '   time: ', 14786.133425951004)
('Valid: ', '85.85', 'Valid root: ', '42.78', ' Test all: ', '85.23', 'Test root: ', '38.91', ' Train all: ', '90.89', 'Train root: ', '54.27', '   time: ', 15484.936663866043)
('Best valid: ', '85.97', ' Test all: ', '85.19', 'Test root: ', '35.07', '   time: ', 15484.936718940735)