MDAN/amazon.log at master · thejonathanvancetrance/MDAN · GitHub

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07-29 12:18 [MainProcess, 7088] [INFO ]  Time used to process the Amazon data set = 0.28624558448791504 seconds.
07-29 12:18 [MainProcess, 7088] [INFO ]  Number of training instances = 27677, number of features = 5000.
07-29 12:18 [MainProcess, 7088] [INFO ]  Number of nonzero elements = 2140430
07-29 12:18 [MainProcess, 7088] [INFO ]  amazon_xx shape = (27677, 5000).
07-29 12:18 [MainProcess, 7088] [INFO ]  amazon_yy shape = (27677, 1).
07-29 12:18 [MainProcess, 7088] [INFO ]  Length of the books data set label list = 6465, label values = [0. 1.], label balance = 3264.0
07-29 12:18 [MainProcess, 7088] [INFO ]  Length of the dvd data set label list = 5586, label values = [0. 1.], label balance = 2807.0
07-29 12:18 [MainProcess, 7088] [INFO ]  Length of the electronics data set label list = 7681, label values = [0. 1.], label balance = 3857.0
07-29 12:18 [MainProcess, 7088] [INFO ]  Length of the kitchen data set label list = 7945, label values = [0. 1.], label balance = 3954.0
07-29 12:18 [MainProcess, 7088] [INFO ]  Data sets: ['books', 'dvd', 'electronics', 'kitchen']
07-29 12:18 [MainProcess, 7088] [INFO ]  Number of total instances in the data sets: [6465, 5586, 7681, 7945]
07-29 12:18 [MainProcess, 7088] [INFO ]  Training fraction = 1.0, number of actual training data instances = 2000
07-29 12:18 [MainProcess, 7088] [INFO ]  ----------------------------------------------------------------------------------------------------
07-29 12:18 [MainProcess, 7088] [INFO ]  Training with domain adaptation using PyTorch madnNet:
07-29 12:18 [MainProcess, 7088] [INFO ]  Hyperparameter setting = {'input_dim': 5000, 'hidden_layers': [1000, 500, 100], 'num_classes': 2, 'num_epochs': 15, 'batch_size': 20, 'lr': 1.0, 'mu': 0.01, 'num_domains': 3, 'mode': 'maxmin', 'gamma': 10.0, 'verbose': True}.
07-29 12:20 [MainProcess, 14164] [INFO ]  Time used to process the Amazon data set = 0.250030517578125 seconds.
07-29 12:20 [MainProcess, 14164] [INFO ]  Number of training instances = 27677, number of features = 5000.
07-29 12:20 [MainProcess, 14164] [INFO ]  Number of nonzero elements = 2140430
07-29 12:20 [MainProcess, 14164] [INFO ]  amazon_xx shape = (27677, 5000).
07-29 12:20 [MainProcess, 14164] [INFO ]  amazon_yy shape = (27677, 1).
07-29 12:20 [MainProcess, 14164] [INFO ]  Length of the books data set label list = 6465, label values = [0. 1.], label balance = 3264.0
07-29 12:20 [MainProcess, 14164] [INFO ]  Length of the dvd data set label list = 5586, label values = [0. 1.], label balance = 2807.0
07-29 12:20 [MainProcess, 14164] [INFO ]  Length of the electronics data set label list = 7681, label values = [0. 1.], label balance = 3857.0
07-29 12:20 [MainProcess, 14164] [INFO ]  Length of the kitchen data set label list = 7945, label values = [0. 1.], label balance = 3954.0
07-29 12:20 [MainProcess, 14164] [INFO ]  Data sets: ['books', 'dvd', 'electronics', 'kitchen']
07-29 12:20 [MainProcess, 14164] [INFO ]  Number of total instances in the data sets: [6465, 5586, 7681, 7945]
07-29 12:20 [MainProcess, 14164] [INFO ]  Training fraction = 1.0, number of actual training data instances = 2000
07-29 12:20 [MainProcess, 14164] [INFO ]  ----------------------------------------------------------------------------------------------------
07-29 12:20 [MainProcess, 14164] [INFO ]  Training with domain adaptation using PyTorch madnNet:
07-29 12:20 [MainProcess, 14164] [INFO ]  Hyperparameter setting = {'input_dim': 5000, 'hidden_layers': [1000, 500, 100], 'num_classes': 2, 'num_epochs': 15, 'batch_size': 20, 'lr': 1.0, 'mu': 0.01, 'num_domains': 3, 'mode': 'maxmin', 'gamma': 10.0, 'verbose': True}.
07-29 12:20 [MainProcess, 20856] [INFO ]  Time used to process the Amazon data set = 0.25997042655944824 seconds.
07-29 12:20 [MainProcess, 20856] [INFO ]  Number of training instances = 27677, number of features = 5000.
07-29 12:20 [MainProcess, 20856] [INFO ]  Number of nonzero elements = 2140430
07-29 12:20 [MainProcess, 20856] [INFO ]  amazon_xx shape = (27677, 5000).
07-29 12:20 [MainProcess, 20856] [INFO ]  amazon_yy shape = (27677, 1).
07-29 12:20 [MainProcess, 20856] [INFO ]  Length of the books data set label list = 6465, label values = [0. 1.], label balance = 3264.0
07-29 12:20 [MainProcess, 20856] [INFO ]  Length of the dvd data set label list = 5586, label values = [0. 1.], label balance = 2807.0
07-29 12:20 [MainProcess, 20856] [INFO ]  Length of the electronics data set label list = 7681, label values = [0. 1.], label balance = 3857.0
07-29 12:20 [MainProcess, 20856] [INFO ]  Length of the kitchen data set label list = 7945, label values = [0. 1.], label balance = 3954.0
07-29 12:20 [MainProcess, 20856] [INFO ]  Data sets: ['books', 'dvd', 'electronics', 'kitchen']
07-29 12:20 [MainProcess, 20856] [INFO ]  Number of total instances in the data sets: [6465, 5586, 7681, 7945]
07-29 12:20 [MainProcess, 20856] [INFO ]  Training fraction = 1.0, number of actual training data instances = 2000
07-29 12:20 [MainProcess, 20856] [INFO ]  ----------------------------------------------------------------------------------------------------
07-29 12:20 [MainProcess, 20856] [INFO ]  Training with domain adaptation using PyTorch madnNet:
07-29 12:20 [MainProcess, 20856] [INFO ]  Hyperparameter setting = {'input_dim': 5000, 'hidden_layers': [1000, 500, 100], 'num_classes': 2, 'num_epochs': 15, 'batch_size': 20, 'lr': 1.0, 'mu': 0.01, 'num_domains': 3, 'mode': 'maxmin', 'gamma': 10.0, 'verbose': True}.
07-29 12:24 [MainProcess, 15860] [INFO ]  Time used to process the Amazon data set = 0.24605607986450195 seconds.
07-29 12:24 [MainProcess, 15860] [INFO ]  Number of training instances = 27677, number of features = 5000.
07-29 12:24 [MainProcess, 15860] [INFO ]  Number of nonzero elements = 2140430
07-29 12:24 [MainProcess, 15860] [INFO ]  amazon_xx shape = (27677, 5000).
07-29 12:24 [MainProcess, 15860] [INFO ]  amazon_yy shape = (27677, 1).
07-29 12:24 [MainProcess, 15860] [INFO ]  Length of the books data set label list = 6465, label values = [0. 1.], label balance = 3264.0
07-29 12:24 [MainProcess, 15860] [INFO ]  Length of the dvd data set label list = 5586, label values = [0. 1.], label balance = 2807.0
07-29 12:24 [MainProcess, 15860] [INFO ]  Length of the electronics data set label list = 7681, label values = [0. 1.], label balance = 3857.0
07-29 12:24 [MainProcess, 15860] [INFO ]  Length of the kitchen data set label list = 7945, label values = [0. 1.], label balance = 3954.0
07-29 12:24 [MainProcess, 15860] [INFO ]  Data sets: ['books', 'dvd', 'electronics', 'kitchen']
07-29 12:24 [MainProcess, 15860] [INFO ]  Number of total instances in the data sets: [6465, 5586, 7681, 7945]
07-29 12:24 [MainProcess, 15860] [INFO ]  Training fraction = 1.0, number of actual training data instances = 2000
07-29 12:24 [MainProcess, 15860] [INFO ]  ----------------------------------------------------------------------------------------------------
07-29 12:24 [MainProcess, 15860] [INFO ]  Training with domain adaptation using PyTorch madnNet:
07-29 12:24 [MainProcess, 15860] [INFO ]  Hyperparameter setting = {'input_dim': 5000, 'hidden_layers': [1000, 500, 100], 'num_classes': 2, 'num_epochs': 15, 'batch_size': 20, 'lr': 1.0, 'mu': 0.01, 'num_domains': 3, 'mode': 'maxmin', 'gamma': 10.0, 'verbose': True}.
07-29 12:25 [MainProcess, 9536] [INFO ]  Time used to process the Amazon data set = 0.2376255989074707 seconds.
07-29 12:25 [MainProcess, 9536] [INFO ]  Number of training instances = 27677, number of features = 5000.
07-29 12:25 [MainProcess, 9536] [INFO ]  Number of nonzero elements = 2140430
07-29 12:25 [MainProcess, 9536] [INFO ]  amazon_xx shape = (27677, 5000).
07-29 12:25 [MainProcess, 9536] [INFO ]  amazon_yy shape = (27677, 1).
07-29 12:25 [MainProcess, 9536] [INFO ]  Length of the books data set label list = 6465, label values = [0. 1.], label balance = 3264.0
07-29 12:25 [MainProcess, 9536] [INFO ]  Length of the dvd data set label list = 5586, label values = [0. 1.], label balance = 2807.0
07-29 12:25 [MainProcess, 9536] [INFO ]  Length of the electronics data set label list = 7681, label values = [0. 1.], label balance = 3857.0
07-29 12:25 [MainProcess, 9536] [INFO ]  Length of the kitchen data set label list = 7945, label values = [0. 1.], label balance = 3954.0
07-29 12:25 [MainProcess, 9536] [INFO ]  Data sets: ['books', 'dvd', 'electronics', 'kitchen']
07-29 12:25 [MainProcess, 9536] [INFO ]  Number of total instances in the data sets: [6465, 5586, 7681, 7945]
07-29 12:25 [MainProcess, 9536] [INFO ]  Training fraction = 1.0, number of actual training data instances = 2000
07-29 12:25 [MainProcess, 9536] [INFO ]  ----------------------------------------------------------------------------------------------------
07-29 12:25 [MainProcess, 9536] [INFO ]  Training with domain adaptation using PyTorch madnNet:
07-29 12:25 [MainProcess, 9536] [INFO ]  Hyperparameter setting = {'input_dim': 5000, 'hidden_layers': [1000, 500, 100], 'num_classes': 2, 'num_epochs': 15, 'batch_size': 20, 'lr': 1.0, 'mu': 0.01, 'num_domains': 3, 'mode': 'maxmin', 'gamma': 10.0, 'verbose': True}.
07-29 12:25 [MainProcess, 18924] [INFO ]  Time used to process the Amazon data set = 0.24025869369506836 seconds.
07-29 12:25 [MainProcess, 18924] [INFO ]  Number of training instances = 27677, number of features = 5000.
07-29 12:25 [MainProcess, 18924] [INFO ]  Number of nonzero elements = 2140430
07-29 12:25 [MainProcess, 18924] [INFO ]  amazon_xx shape = (27677, 5000).
07-29 12:25 [MainProcess, 18924] [INFO ]  amazon_yy shape = (27677, 1).
07-29 12:25 [MainProcess, 18924] [INFO ]  Length of the books data set label list = 6465, label values = [0. 1.], label balance = 3264.0
07-29 12:25 [MainProcess, 18924] [INFO ]  Length of the dvd data set label list = 5586, label values = [0. 1.], label balance = 2807.0
07-29 12:25 [MainProcess, 18924] [INFO ]  Length of the electronics data set label list = 7681, label values = [0. 1.], label balance = 3857.0
07-29 12:25 [MainProcess, 18924] [INFO ]  Length of the kitchen data set label list = 7945, label values = [0. 1.], label balance = 3954.0
07-29 12:25 [MainProcess, 18924] [INFO ]  Data sets: ['books', 'dvd', 'electronics', 'kitchen']
07-29 12:25 [MainProcess, 18924] [INFO ]  Number of total instances in the data sets: [6465, 5586, 7681, 7945]
07-29 12:25 [MainProcess, 18924] [INFO ]  Training fraction = 1.0, number of actual training data instances = 2000
07-29 12:25 [MainProcess, 18924] [INFO ]  ----------------------------------------------------------------------------------------------------
07-29 12:25 [MainProcess, 18924] [INFO ]  Training with domain adaptation using PyTorch madnNet:
07-29 12:25 [MainProcess, 18924] [INFO ]  Hyperparameter setting = {'input_dim': 5000, 'hidden_layers': [1000, 500, 100], 'num_classes': 2, 'num_epochs': 15, 'batch_size': 20, 'lr': 1.0, 'mu': 0.01, 'num_domains': 3, 'mode': 'maxmin', 'gamma': 10.0, 'verbose': True}.
07-29 12:27 [MainProcess, 12940] [INFO ]  Time used to process the Amazon data set = 0.24141836166381836 seconds.
07-29 12:27 [MainProcess, 12940] [INFO ]  Number of training instances = 27677, number of features = 5000.
07-29 12:27 [MainProcess, 12940] [INFO ]  Number of nonzero elements = 2140430
07-29 12:27 [MainProcess, 12940] [INFO ]  amazon_xx shape = (27677, 5000).
07-29 12:27 [MainProcess, 12940] [INFO ]  amazon_yy shape = (27677, 1).
07-29 12:27 [MainProcess, 12940] [INFO ]  Length of the books data set label list = 6465, label values = [0. 1.], label balance = 3264.0
07-29 12:27 [MainProcess, 12940] [INFO ]  Length of the dvd data set label list = 5586, label values = [0. 1.], label balance = 2807.0
07-29 12:27 [MainProcess, 12940] [INFO ]  Length of the electronics data set label list = 7681, label values = [0. 1.], label balance = 3857.0
07-29 12:27 [MainProcess, 12940] [INFO ]  Length of the kitchen data set label list = 7945, label values = [0. 1.], label balance = 3954.0
07-29 12:27 [MainProcess, 12940] [INFO ]  Data sets: ['books', 'dvd', 'electronics', 'kitchen']
07-29 12:27 [MainProcess, 12940] [INFO ]  Number of total instances in the data sets: [6465, 5586, 7681, 7945]
07-29 12:27 [MainProcess, 12940] [INFO ]  Training fraction = 1.0, number of actual training data instances = 2000
07-29 12:27 [MainProcess, 12940] [INFO ]  ----------------------------------------------------------------------------------------------------
07-29 12:27 [MainProcess, 12940] [INFO ]  Training with domain adaptation using PyTorch madnNet:
07-29 12:27 [MainProcess, 12940] [INFO ]  Hyperparameter setting = {'input_dim': 5000, 'hidden_layers': [1000, 500, 100], 'num_classes': 2, 'num_epochs': 15, 'batch_size': 20, 'lr': 1.0, 'mu': 0.01, 'num_domains': 3, 'mode': 'maxmin', 'gamma': 10.0, 'verbose': True}.
07-29 12:32 [MainProcess, 17952] [INFO ]  Time used to process the Amazon data set = 0.23688125610351562 seconds.
07-29 12:32 [MainProcess, 17952] [INFO ]  Number of training instances = 27677, number of features = 5000.
07-29 12:32 [MainProcess, 17952] [INFO ]  Number of nonzero elements = 2140430
07-29 12:32 [MainProcess, 17952] [INFO ]  amazon_xx shape = (27677, 5000).
07-29 12:32 [MainProcess, 17952] [INFO ]  amazon_yy shape = (27677, 1).
07-29 12:32 [MainProcess, 17952] [INFO ]  Length of the books data set label list = 6465, label values = [0. 1.], label balance = 3264.0
07-29 12:32 [MainProcess, 17952] [INFO ]  Length of the dvd data set label list = 5586, label values = [0. 1.], label balance = 2807.0
07-29 12:32 [MainProcess, 17952] [INFO ]  Length of the electronics data set label list = 7681, label values = [0. 1.], label balance = 3857.0
07-29 12:32 [MainProcess, 17952] [INFO ]  Length of the kitchen data set label list = 7945, label values = [0. 1.], label balance = 3954.0
07-29 12:32 [MainProcess, 17952] [INFO ]  Data sets: ['books', 'dvd', 'electronics', 'kitchen']
07-29 12:32 [MainProcess, 17952] [INFO ]  Number of total instances in the data sets: [6465, 5586, 7681, 7945]
07-29 12:32 [MainProcess, 17952] [INFO ]  Training fraction = 1.0, number of actual training data instances = 2000
07-29 12:32 [MainProcess, 17952] [INFO ]  ----------------------------------------------------------------------------------------------------
07-29 12:32 [MainProcess, 17952] [INFO ]  Training with domain adaptation using PyTorch madnNet:
07-29 12:32 [MainProcess, 17952] [INFO ]  Hyperparameter setting = {'input_dim': 5000, 'hidden_layers': [1000, 500, 100], 'num_classes': 2, 'num_epochs': 15, 'batch_size': 20, 'lr': 1.0, 'mu': 0.01, 'num_domains': 3, 'mode': 'maxmin', 'gamma': 10.0, 'verbose': True}.
07-29 12:34 [MainProcess, 20344] [INFO ]  Time used to process the Amazon data set = 0.24027609825134277 seconds.
07-29 12:34 [MainProcess, 20344] [INFO ]  Number of training instances = 27677, number of features = 5000.
07-29 12:34 [MainProcess, 20344] [INFO ]  Number of nonzero elements = 2140430
07-29 12:34 [MainProcess, 20344] [INFO ]  amazon_xx shape = (27677, 5000).
07-29 12:34 [MainProcess, 20344] [INFO ]  amazon_yy shape = (27677, 1).
07-29 12:34 [MainProcess, 20344] [INFO ]  Length of the books data set label list = 6465, label values = [0. 1.], label balance = 3264.0
07-29 12:34 [MainProcess, 20344] [INFO ]  Length of the dvd data set label list = 5586, label values = [0. 1.], label balance = 2807.0
07-29 12:34 [MainProcess, 20344] [INFO ]  Length of the electronics data set label list = 7681, label values = [0. 1.], label balance = 3857.0
07-29 12:34 [MainProcess, 20344] [INFO ]  Length of the kitchen data set label list = 7945, label values = [0. 1.], label balance = 3954.0
07-29 12:34 [MainProcess, 20344] [INFO ]  Data sets: ['books', 'dvd', 'electronics', 'kitchen']
07-29 12:34 [MainProcess, 20344] [INFO ]  Number of total instances in the data sets: [6465, 5586, 7681, 7945]
07-29 12:34 [MainProcess, 20344] [INFO ]  Training fraction = 1.0, number of actual training data instances = 2000
07-29 12:34 [MainProcess, 20344] [INFO ]  ----------------------------------------------------------------------------------------------------
07-29 12:34 [MainProcess, 20344] [INFO ]  Training with domain adaptation using PyTorch madnNet:
07-29 12:34 [MainProcess, 20344] [INFO ]  Hyperparameter setting = {'input_dim': 5000, 'hidden_layers': [1000, 500, 100], 'num_classes': 2, 'num_epochs': 15, 'batch_size': 20, 'lr': 1.0, 'mu': 0.01, 'num_domains': 3, 'mode': 'maxmin', 'gamma': 10.0, 'verbose': True}.
07-29 12:35 [MainProcess, 20344] [INFO ]  Iteration 0, loss = 64.44407433271408
07-29 12:35 [MainProcess, 20344] [INFO ]  Iteration 1, loss = 45.76395523548126
07-29 12:35 [MainProcess, 20344] [INFO ]  Iteration 2, loss = 34.72406619787216
07-29 12:36 [MainProcess, 20344] [INFO ]  Iteration 3, loss = 26.09684456139803
07-29 12:36 [MainProcess, 20344] [INFO ]  Iteration 4, loss = 19.979970525950193
07-29 12:36 [MainProcess, 20344] [INFO ]  Iteration 5, loss = 15.06159595772624
07-29 12:37 [MainProcess, 20344] [INFO ]  Iteration 6, loss = 10.421774109825492
07-29 12:37 [MainProcess, 20344] [INFO ]  Iteration 7, loss = 6.766052357852459
07-29 12:37 [MainProcess, 20344] [INFO ]  Iteration 8, loss = 6.267294947057962
07-29 12:38 [MainProcess, 20344] [INFO ]  Iteration 9, loss = 2.7029820969328284
07-29 12:38 [MainProcess, 20344] [INFO ]  Iteration 10, loss = 1.9982818104326725
07-29 12:38 [MainProcess, 20344] [INFO ]  Iteration 11, loss = 1.7694151420146227
07-29 12:39 [MainProcess, 20344] [INFO ]  Iteration 12, loss = 1.4293137034401298
07-29 12:39 [MainProcess, 20344] [INFO ]  Iteration 13, loss = 1.422861635684967
07-29 12:39 [MainProcess, 20344] [INFO ]  Iteration 14, loss = 2.1146598178893328
07-29 12:39 [MainProcess, 20344] [INFO ]  Prediction accuracy on books = 0.7832026875699888, time used = 285.6193814277649 seconds.
07-29 12:39 [MainProcess, 20344] [INFO ]  Iteration 0, loss = 66.54645112156868
07-29 12:40 [MainProcess, 20344] [INFO ]  Iteration 1, loss = 46.751883298158646
07-29 12:40 [MainProcess, 20344] [INFO ]  Iteration 2, loss = 37.58391232788563
07-29 12:40 [MainProcess, 20344] [INFO ]  Iteration 3, loss = 28.75340484827757
07-29 12:41 [MainProcess, 20344] [INFO ]  Iteration 4, loss = 21.193372890353203
07-29 12:41 [MainProcess, 20344] [INFO ]  Iteration 5, loss = 14.685051139444113