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adv_model_comp_log.out
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adv_model_comp_log.out
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2020-06-26 21:07:02
Gold-Mart Dependency Parser
-------------------------------------------------------------------------------------------
word_embd_dim = 300
pos_embd_dim = 100
word_hidden_dim = 125
MLP_inner_dim = 100
char_emb_dim = 80
char_hidden_dim = 50
epochs = 30
learning_rate = 0.01
dropout_layers_probability = 0.0
weight_decay = 1e-05
alpha = 0.25
min_freq = 3
BiLSTM_layers = 3
use_pre_trained = False
vectors =
path_train = train_5700_sentences.labeled
path_test = test_300_sentences.labeled
Training Started
Epoch 1 Completed, Train Loss 0.49456932758209865 Train Accuracy: 0.8610224398660375 Test Loss 0.5665251836397995 Test Accuracy: 0.8391795072731771
Epoch 1 Time 2020-06-26 21:12:36
Epoch 2 Completed, Train Loss 0.3289100298644942 Train Accuracy: 0.9009627441057102 Test Loss 0.4281431983128035 Test Accuracy: 0.8806680776887548
Epoch 2 Time 2020-06-26 21:16:58
Epoch 3 Completed, Train Loss 0.27467371237621513 Train Accuracy: 0.9201904063840303 Test Loss 0.3927709343152431 Test Accuracy: 0.8920928286861384
Epoch 3 Time 2020-06-26 21:21:21
Epoch 4 Completed, Train Loss 0.2347352074367799 Train Accuracy: 0.9292340066697822 Test Loss 0.3735052981266441 Test Accuracy: 0.8908452922524144
Epoch 4 Time 2020-06-26 21:25:41
Epoch 5 Completed, Train Loss 0.2042865910028131 Train Accuracy: 0.9372527275634236 Test Loss 0.3425266669337482 Test Accuracy: 0.8987183012777026
Epoch 5 Time 2020-06-26 21:29:57
Epoch 6 Completed, Train Loss 0.18257575899569353 Train Accuracy: 0.9436463903027781 Test Loss 0.3365349004101396 Test Accuracy: 0.9025933194194967
Epoch 6 Time 2020-06-26 21:34:16
Epoch 7 Completed, Train Loss 0.1755869275093918 Train Accuracy: 0.9455598905212802 Test Loss 0.3577466704294784 Test Accuracy: 0.9031637604371879
Epoch 7 Time 2020-06-26 21:39:44
Epoch 8 Completed, Train Loss 0.1567786209928505 Train Accuracy: 0.9512737922406491 Test Loss 0.34511112510381886 Test Accuracy: 0.902866021776775
Epoch 8 Time 2020-06-26 21:45:44
Epoch 9 Completed, Train Loss 0.13814272558427132 Train Accuracy: 0.9568041536958123 Test Loss 0.34547876312872783 Test Accuracy: 0.90433303069076
Epoch 9 Time 2020-06-26 21:51:43
Epoch 10 Completed, Train Loss 0.14279876859889587 Train Accuracy: 0.9544177921844664 Test Loss 0.34329009475686084 Test Accuracy: 0.9049582672462988
Epoch 10 Time 2020-06-26 21:57:47
Epoch 11 Completed, Train Loss 0.12425352633772714 Train Accuracy: 0.9610084724068151 Test Loss 0.346086526654326 Test Accuracy: 0.9096083559351519
Epoch 11 Time 2020-06-26 22:03:51
Epoch 12 Completed, Train Loss 0.13110254607487276 Train Accuracy: 0.9586703186520444 Test Loss 0.3626812590859724 Test Accuracy: 0.9052754408793053
Epoch 12 Time 2020-06-26 22:09:45
Epoch 13 Completed, Train Loss 0.11630749274007636 Train Accuracy: 0.9637011497465455 Test Loss 0.3419227019680693 Test Accuracy: 0.9054507946164764
Epoch 13 Time 2020-06-26 22:14:04
Epoch 14 Completed, Train Loss 0.11089890936738811 Train Accuracy: 0.9650639039476415 Test Loss 0.3599697178428566 Test Accuracy: 0.9077933441579443
Epoch 14 Time 2020-06-26 22:18:20
Epoch 15 Completed, Train Loss 0.11061974631678599 Train Accuracy: 0.9657271285678455 Test Loss 0.36070659184178416 Test Accuracy: 0.9055173863901925
Epoch 15 Time 2020-06-26 22:22:37
Epoch 16 Completed, Train Loss 0.11740789293248606 Train Accuracy: 0.9628474286864368 Test Loss 0.3786340454176631 Test Accuracy: 0.9028798755365985
Epoch 16 Time 2020-06-26 22:26:56
Epoch 17 Completed, Train Loss 0.11298131043514954 Train Accuracy: 0.964574106645576 Test Loss 0.35474760558116636 Test Accuracy: 0.9077603045573487
Epoch 17 Time 2020-06-26 22:31:14
Epoch 18 Completed, Train Loss 0.09616715184220435 Train Accuracy: 0.9698337376623786 Test Loss 0.35624526148369723 Test Accuracy: 0.9070001678997331
Epoch 18 Time 2020-06-26 22:35:30
Epoch 19 Completed, Train Loss 0.094945582336079 Train Accuracy: 0.9703235036578481 Test Loss 0.34894479820250124 Test Accuracy: 0.9108563560952818
Epoch 19 Time 2020-06-26 22:39:47
Epoch 20 Completed, Train Loss 0.09171058678468 Train Accuracy: 0.9708273470391696 Test Loss 0.376995775409038 Test Accuracy: 0.9084299118040849
Epoch 20 Time 2020-06-26 22:44:04
Epoch 21 Completed, Train Loss 0.11088261027962769 Train Accuracy: 0.9655820225248569 Test Loss 0.3538906495608535 Test Accuracy: 0.905586854615214
Epoch 21 Time 2020-06-26 22:48:21
Epoch 22 Completed, Train Loss 0.09977220103718808 Train Accuracy: 0.9686260623437234 Test Loss 0.37512758726632456 Test Accuracy: 0.900611153415194
Epoch 22 Time 2020-06-26 22:52:38
Epoch 23 Completed, Train Loss 0.0993129837983884 Train Accuracy: 0.9690749385971342 Test Loss 0.3678116125747329 Test Accuracy: 0.9079665765013116
Epoch 23 Time 2020-06-26 22:56:56
Epoch 24 Completed, Train Loss 0.09717841666300732 Train Accuracy: 0.9691704309502469 Test Loss 0.37366033742104265 Test Accuracy: 0.9081100554484192
Epoch 24 Time 2020-06-26 23:01:14
Epoch 25 Completed, Train Loss 0.07179649460995183 Train Accuracy: 0.9783648755495279 Test Loss 0.353577612130357 Test Accuracy: 0.9153108925386197
Epoch 25 Time 2020-06-26 23:05:30
Epoch 26 Completed, Train Loss 0.07591357482682916 Train Accuracy: 0.9767057344807937 Test Loss 0.3753415924119205 Test Accuracy: 0.9131540328631392
Epoch 26 Time 2020-06-26 23:09:48
Epoch 27 Completed, Train Loss 0.08034506645080255 Train Accuracy: 0.9743990061998319 Test Loss 0.36148606857377064 Test Accuracy: 0.9143133401736387
Epoch 27 Time 2020-06-26 23:14:05
Epoch 28 Completed, Train Loss 0.06444765716592085 Train Accuracy: 0.9801208422803794 Test Loss 0.3846189903010236 Test Accuracy: 0.9122402657356168
Epoch 28 Time 2020-06-26 23:18:23
Epoch 29 Completed, Train Loss 0.08246942935599037 Train Accuracy: 0.9740463384285003 Test Loss 0.39513228381768084 Test Accuracy: 0.9105045107515171
Epoch 29 Time 2020-06-26 23:22:41
Epoch 30 Completed, Train Loss 0.07671681335432623 Train Accuracy: 0.9762378046825638 Test Loss 0.39715505910836024 Test Accuracy: 0.909179559432668
Epoch 30 Time 2020-06-26 23:27:00
total_train_time = 5738 SECS total_evaluate_time (train and test) = 2658 SECS
train_accuracy_list = [0.8610224398660375, 0.9009627441057102, 0.9201904063840303, 0.9292340066697822, 0.9372527275634236, 0.9436463903027781, 0.9455598905212802, 0.9512737922406491, 0.9568041536958123, 0.9544177921844664, 0.9610084724068151, 0.9586703186520444, 0.9637011497465455, 0.9650639039476415, 0.9657271285678455, 0.9628474286864368, 0.964574106645576, 0.9698337376623786, 0.9703235036578481, 0.9708273470391696, 0.9655820225248569, 0.9686260623437234, 0.9690749385971342, 0.9691704309502469, 0.9783648755495279, 0.9767057344807937, 0.9743990061998319, 0.9801208422803794, 0.9740463384285003, 0.9762378046825638]
train_loss_list = [0.49456932758209865, 0.3289100298644942, 0.27467371237621513, 0.2347352074367799, 0.2042865910028131, 0.18257575899569353, 0.1755869275093918, 0.1567786209928505, 0.13814272558427132, 0.14279876859889587, 0.12425352633772714, 0.13110254607487276, 0.11630749274007636, 0.11089890936738811, 0.11061974631678599, 0.11740789293248606, 0.11298131043514954, 0.09616715184220435, 0.094945582336079, 0.09171058678468, 0.11088261027962769, 0.09977220103718808, 0.0993129837983884, 0.09717841666300732, 0.07179649460995183, 0.07591357482682916, 0.08034506645080255, 0.06444765716592085, 0.08246942935599037, 0.07671681335432623]
test_accuracy_list = [0.8391795072731771, 0.8806680776887548, 0.8920928286861384, 0.8908452922524144, 0.8987183012777026, 0.9025933194194967, 0.9031637604371879, 0.902866021776775, 0.90433303069076, 0.9049582672462988, 0.9096083559351519, 0.9052754408793053, 0.9054507946164764, 0.9077933441579443, 0.9055173863901925, 0.9028798755365985, 0.9077603045573487, 0.9070001678997331, 0.9108563560952818, 0.9084299118040849, 0.905586854615214, 0.900611153415194, 0.9079665765013116, 0.9081100554484192, 0.9153108925386197, 0.9131540328631392, 0.9143133401736387, 0.9122402657356168, 0.9105045107515171, 0.909179559432668]
test_loss_list = [0.5665251836397995, 0.4281431983128035, 0.3927709343152431, 0.3735052981266441, 0.3425266669337482, 0.3365349004101396, 0.3577466704294784, 0.34511112510381886, 0.34547876312872783, 0.34329009475686084, 0.346086526654326, 0.3626812590859724, 0.3419227019680693, 0.3599697178428566, 0.36070659184178416, 0.3786340454176631, 0.35474760558116636, 0.35624526148369723, 0.34894479820250124, 0.376995775409038, 0.3538906495608535, 0.37512758726632456, 0.3678116125747329, 0.37366033742104265, 0.353577612130357, 0.3753415924119205, 0.36148606857377064, 0.3846189903010236, 0.39513228381768084, 0.39715505910836024]