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GraphTransformer(
(embedding): Linear(in_features=4096, out_features=256, bias=False)
(encoder): GraphTransformerEncoder(
(layers): ModuleList(
(0-2): 3 x TransformerEncoderLayer(
(self_attn): Attention()
(linear1): Linear(in_features=256, out_features=128, bias=True)
(dropout): Dropout(p=0.1, inplace=False)
(linear2): Linear(in_features=128, out_features=256, bias=True)
(norm1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(norm2): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(dropout1): Dropout(p=0.1, inplace=False)
(dropout2): Dropout(p=0.1, inplace=False)
)
)
)
(classifier): Sequential(
(0): Linear(in_features=256, out_features=256, bias=True)
(1): ReLU(inplace=True)
(2): Linear(in_features=256, out_features=2, bias=True)
)
)
Total number of parameters: 3096706
Extracting 2-hop subgraphs...
Done!
Extracting 2-hop subgraphs...
Done!
Training...
Train 1/300, loss 0.4991, time 0.8682
Val 1/300, loss 0.6436, time 0.0913 | acc 0.6102 | pre 0.6102 | recall 1.0000 | f1 0.7579
Train 2/300, loss 0.3110, time 0.6567
Val 2/300, loss 0.6282, time 0.0774 | acc 0.7966 | pre 0.7727 | recall 0.9444 | f1 0.8500
Train 3/300, loss 0.2227, time 0.6347
Val 3/300, loss 0.5816, time 0.0778 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 4/300, loss 0.1930, time 0.6380
Val 4/300, loss 0.5348, time 0.0778 | acc 0.8305 | pre 0.7955 | recall 0.9722 | f1 0.8750
Train 5/300, loss 0.1545, time 0.6284
Val 5/300, loss 0.4773, time 0.0772 | acc 0.8475 | pre 0.8649 | recall 0.8889 | f1 0.8767
Train 6/300, loss 0.1345, time 0.6195
Val 6/300, loss 0.4291, time 0.0773 | acc 0.7966 | pre 0.9000 | recall 0.7500 | f1 0.8182
Train 7/300, loss 0.1228, time 0.6491
Val 7/300, loss 0.3784, time 0.0785 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 8/300, loss 0.1031, time 0.6258
Val 8/300, loss 0.3662, time 0.0763 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 9/300, loss 0.1117, time 0.6235
Val 9/300, loss 0.3563, time 0.0767 | acc 0.8814 | pre 0.8919 | recall 0.9167 | f1 0.9041
Train 10/300, loss 0.0922, time 0.6228
Val 10/300, loss 0.4213, time 0.0821 | acc 0.8644 | pre 0.8889 | recall 0.8889 | f1 0.8889
Train 11/300, loss 0.0656, time 0.6459
Val 11/300, loss 0.4346, time 0.0758 | acc 0.8814 | pre 0.8919 | recall 0.9167 | f1 0.9041
Train 12/300, loss 0.0664, time 0.6298
Val 12/300, loss 0.4267, time 0.0756 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 13/300, loss 0.0671, time 0.6203
Val 13/300, loss 0.9572, time 0.0760 | acc 0.8305 | pre 0.9333 | recall 0.7778 | f1 0.8485
Train 14/300, loss 0.0850, time 0.5904
Val 14/300, loss 0.6839, time 0.0755 | acc 0.8983 | pre 0.9412 | recall 0.8889 | f1 0.9143
Train 15/300, loss 0.0958, time 0.6291
Val 15/300, loss 0.8358, time 0.0759 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 16/300, loss 0.0643, time 0.6349
Val 16/300, loss 0.7891, time 0.0763 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 17/300, loss 0.0437, time 0.6227
Val 17/300, loss 0.8164, time 0.0761 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 18/300, loss 0.0327, time 0.6248
Val 18/300, loss 0.7487, time 0.0768 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 19/300, loss 0.0236, time 0.6285
Val 19/300, loss 0.6713, time 0.0759 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 20/300, loss 0.0237, time 0.6286
Val 20/300, loss 0.6766, time 0.0773 | acc 0.9153 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 21/300, loss 0.0232, time 0.6137
Val 21/300, loss 0.7327, time 0.0747 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 22/300, loss 0.0233, time 0.6154
Val 22/300, loss 0.8054, time 0.0767 | acc 0.8814 | pre 0.8919 | recall 0.9167 | f1 0.9041
Train 23/300, loss 0.0329, time 0.6352
Val 23/300, loss 0.6989, time 0.0743 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 24/300, loss 0.0620, time 0.6101
Val 24/300, loss 0.8501, time 0.0733 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 25/300, loss 0.0416, time 0.6309
Val 25/300, loss 1.0525, time 0.0757 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 26/300, loss 0.0376, time 0.6025
Val 26/300, loss 0.8488, time 0.0752 | acc 0.8983 | pre 0.9412 | recall 0.8889 | f1 0.9143
Train 27/300, loss 0.0268, time 0.6255
Val 27/300, loss 0.7718, time 0.0766 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 28/300, loss 0.0204, time 0.7053
Val 28/300, loss 0.7650, time 0.0780 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 29/300, loss 0.0253, time 0.6400
Val 29/300, loss 0.8359, time 0.0786 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 30/300, loss 0.0399, time 0.6320
Val 30/300, loss 0.9927, time 0.0747 | acc 0.8814 | pre 0.9394 | recall 0.8611 | f1 0.8986
Train 31/300, loss 0.0164, time 0.6186
Val 31/300, loss 0.8253, time 0.0748 | acc 0.8983 | pre 0.9412 | recall 0.8889 | f1 0.9143
Train 32/300, loss 0.0136, time 0.5941
Val 32/300, loss 0.7720, time 0.0744 | acc 0.9153 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 33/300, loss 0.0159, time 0.6230
Val 33/300, loss 0.6544, time 0.0774 | acc 0.9322 | pre 0.9444 | recall 0.9444 | f1 0.9444
Train 34/300, loss 0.0070, time 0.6330
Val 34/300, loss 0.5761, time 0.0745 | acc 0.9153 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 35/300, loss 0.0181, time 0.6319
Val 35/300, loss 0.6058, time 0.0797 | acc 0.9153 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 36/300, loss 0.0154, time 0.7248
Val 36/300, loss 0.7102, time 0.0751 | acc 0.9153 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 37/300, loss 0.0063, time 0.5610
Val 37/300, loss 0.7535, time 0.0753 | acc 0.9322 | pre 0.9444 | recall 0.9444 | f1 0.9444
Train 38/300, loss 0.0059, time 0.6813
Val 38/300, loss 0.7791, time 0.0719 | acc 0.9153 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 39/300, loss 0.0072, time 0.5289
Val 39/300, loss 0.8138, time 0.0739 | acc 0.9153 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 40/300, loss 0.0040, time 0.5305
Val 40/300, loss 0.7988, time 0.0752 | acc 0.8983 | pre 0.9412 | recall 0.8889 | f1 0.9143
Train 41/300, loss 0.0081, time 0.6318
Val 41/300, loss 0.7930, time 0.0731 | acc 0.9153 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 42/300, loss 0.0104, time 0.6167
Val 42/300, loss 0.7539, time 0.0750 | acc 0.8983 | pre 0.9412 | recall 0.8889 | f1 0.9143
Train 43/300, loss 0.0065, time 0.5969
Val 43/300, loss 0.7609, time 0.0730 | acc 0.8983 | pre 0.9412 | recall 0.8889 | f1 0.9143
Train 44/300, loss 0.0097, time 0.6119
Val 44/300, loss 0.6898, time 0.0750 | acc 0.9153 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 45/300, loss 0.0052, time 0.6240
Val 45/300, loss 0.6971, time 0.0750 | acc 0.9322 | pre 0.9444 | recall 0.9444 | f1 0.9444
Train 46/300, loss 0.0101, time 0.6247
Val 46/300, loss 0.6730, time 0.0757 | acc 0.9322 | pre 0.9444 | recall 0.9444 | f1 0.9444
Train 47/300, loss 0.0298, time 0.6718
Val 47/300, loss 0.8101, time 0.0736 | acc 0.9322 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 48/300, loss 0.0128, time 0.6177
Val 48/300, loss 0.9132, time 0.0770 | acc 0.8136 | pre 0.7778 | recall 0.9722 | f1 0.8642
Train 49/300, loss 0.0074, time 0.6368
Val 49/300, loss 0.6196, time 0.0771 | acc 0.9322 | pre 0.9444 | recall 0.9444 | f1 0.9444
Train 50/300, loss 0.0030, time 0.6247
Val 50/300, loss 0.6744, time 0.0770 | acc 0.9153 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 51/300, loss 0.0237, time 0.6276
Val 51/300, loss 0.6748, time 0.0771 | acc 0.9322 | pre 0.9444 | recall 0.9444 | f1 0.9444
Train 52/300, loss 0.0180, time 0.6267
Val 52/300, loss 0.7182, time 0.0771 | acc 0.8814 | pre 0.9394 | recall 0.8611 | f1 0.8986
Train 53/300, loss 0.0533, time 0.6366
Val 53/300, loss 0.7548, time 0.0783 | acc 0.8983 | pre 0.9412 | recall 0.8889 | f1 0.9143
Train 54/300, loss 0.0701, time 0.6396
Val 54/300, loss 0.7697, time 0.0783 | acc 0.9153 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 55/300, loss 0.0985, time 0.6364
Val 55/300, loss 0.7097, time 0.0780 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 56/300, loss 0.0426, time 0.6315
Val 56/300, loss 0.7106, time 0.0786 | acc 0.8644 | pre 0.8500 | recall 0.9444 | f1 0.8947
Train 57/300, loss 0.0343, time 0.6438
Val 57/300, loss 0.6314, time 0.0781 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 58/300, loss 0.0184, time 0.6337
Val 58/300, loss 0.9355, time 0.0786 | acc 0.8814 | pre 0.9394 | recall 0.8611 | f1 0.8986
Train 59/300, loss 0.0105, time 0.6356
Val 59/300, loss 0.8706, time 0.0782 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 60/300, loss 0.0070, time 0.6380
Val 60/300, loss 0.8159, time 0.0781 | acc 0.8814 | pre 0.9394 | recall 0.8611 | f1 0.8986
Train 61/300, loss 0.0077, time 0.6395
Val 61/300, loss 0.7992, time 0.0781 | acc 0.8983 | pre 0.9412 | recall 0.8889 | f1 0.9143
Train 62/300, loss 0.0051, time 0.6300
Val 62/300, loss 0.7925, time 0.0757 | acc 0.8983 | pre 0.9412 | recall 0.8889 | f1 0.9143
Train 63/300, loss 0.0062, time 0.6329
Val 63/300, loss 0.7752, time 0.0772 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 64/300, loss 0.0035, time 0.6264
Val 64/300, loss 0.7715, time 0.0770 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 65/300, loss 0.0082, time 0.6285
Val 65/300, loss 0.6721, time 0.0771 | acc 0.9153 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 66/300, loss 0.0657, time 0.6220
Val 66/300, loss 0.7504, time 0.0760 | acc 0.8644 | pre 0.8889 | recall 0.8889 | f1 0.8889
Train 67/300, loss 0.0361, time 0.6211
Val 67/300, loss 0.8588, time 0.0765 | acc 0.8814 | pre 0.9394 | recall 0.8611 | f1 0.8986
Train 68/300, loss 0.0424, time 0.6348
Val 68/300, loss 0.9597, time 0.0769 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 69/300, loss 0.0349, time 0.6375
Val 69/300, loss 0.7606, time 0.0764 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 70/300, loss 0.0160, time 0.6363
Val 70/300, loss 0.5715, time 0.0773 | acc 0.9153 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 71/300, loss 0.0284, time 0.6429
Val 71/300, loss 0.6706, time 0.0772 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 72/300, loss 0.0097, time 0.6484
Val 72/300, loss 0.6596, time 0.0769 | acc 0.9322 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 73/300, loss 0.0086, time 0.6404
Val 73/300, loss 0.6290, time 0.0741 | acc 0.9322 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 74/300, loss 0.0121, time 0.6306
Val 74/300, loss 0.7028, time 0.0771 | acc 0.8983 | pre 0.8750 | recall 0.9722 | f1 0.9211
Train 75/300, loss 0.0087, time 0.6524
Val 75/300, loss 0.5867, time 0.0771 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 76/300, loss 0.0037, time 0.6418
Val 76/300, loss 0.7671, time 0.0770 | acc 0.8814 | pre 0.9677 | recall 0.8333 | f1 0.8955
Train 77/300, loss 0.0134, time 0.6353
Val 77/300, loss 1.0581, time 0.0769 | acc 0.8983 | pre 0.8571 | recall 1.0000 | f1 0.9231
Train 78/300, loss 0.0554, time 0.6501
Val 78/300, loss 0.7746, time 0.0770 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 79/300, loss 0.0349, time 0.6299
Val 79/300, loss 6.6850, time 0.0769 | acc 0.4237 | pre 1.0000 | recall 0.0556 | f1 0.1053
Train 80/300, loss 0.0320, time 0.6381
Val 80/300, loss 1.4414, time 0.0773 | acc 0.7458 | pre 0.9565 | recall 0.6111 | f1 0.7458
Train 81/300, loss 0.0290, time 0.6468
Val 81/300, loss 0.7427, time 0.0771 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 82/300, loss 0.0162, time 0.6382
Val 82/300, loss 0.6049, time 0.0770 | acc 0.8983 | pre 0.9412 | recall 0.8889 | f1 0.9143
Train 83/300, loss 0.0090, time 0.6414
Val 83/300, loss 0.6236, time 0.0773 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 84/300, loss 0.0038, time 0.6374
Val 84/300, loss 0.5984, time 0.0758 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 85/300, loss 0.0037, time 0.6486
Val 85/300, loss 0.6702, time 0.0771 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 86/300, loss 0.0022, time 0.6350
Val 86/300, loss 0.6977, time 0.0759 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 87/300, loss 0.0111, time 0.6311
Val 87/300, loss 0.7135, time 0.0758 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 88/300, loss 0.0018, time 0.6434
Val 88/300, loss 0.7598, time 0.0774 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 89/300, loss 0.0022, time 0.6503
Val 89/300, loss 0.8185, time 0.0759 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 90/300, loss 0.0053, time 0.6519
Val 90/300, loss 0.7817, time 0.0775 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 91/300, loss 0.0012, time 0.6416
Val 91/300, loss 0.8126, time 0.0774 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 92/300, loss 0.0016, time 0.6423
Val 92/300, loss 0.8488, time 0.0773 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 93/300, loss 0.0009, time 0.6406
Val 93/300, loss 0.8683, time 0.0772 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 94/300, loss 0.0008, time 0.6440
Val 94/300, loss 0.8960, time 0.0772 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 95/300, loss 0.0010, time 0.6381
Val 95/300, loss 0.9173, time 0.0771 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 96/300, loss 0.0007, time 0.6386
Val 96/300, loss 0.9071, time 0.0776 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 97/300, loss 0.0004, time 0.6396
Val 97/300, loss 0.9070, time 0.0804 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 98/300, loss 0.0006, time 0.6360
Val 98/300, loss 0.9315, time 0.0773 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 99/300, loss 0.0009, time 0.6543
Val 99/300, loss 0.9464, time 0.0771 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 100/300, loss 0.0004, time 0.6526
Val 100/300, loss 0.9196, time 0.0787 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 101/300, loss 0.0006, time 0.6423
Val 101/300, loss 0.9110, time 0.0775 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 102/300, loss 0.0005, time 0.6544
Val 102/300, loss 0.9065, time 0.0775 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 103/300, loss 0.0012, time 0.6449
Val 103/300, loss 0.9193, time 0.0775 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 104/300, loss 0.0006, time 0.6408
Val 104/300, loss 0.9271, time 0.0783 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 105/300, loss 0.0005, time 0.7018
Val 105/300, loss 0.9403, time 0.0740 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 106/300, loss 0.0007, time 0.6485
Val 106/300, loss 0.9294, time 0.0758 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 107/300, loss 0.0004, time 0.6922
Val 107/300, loss 0.9107, time 0.0738 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 108/300, loss 0.0002, time 0.6240
Val 108/300, loss 0.9096, time 0.0761 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 109/300, loss 0.0003, time 0.6606
Val 109/300, loss 0.8922, time 0.0745 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 110/300, loss 0.0005, time 0.6337
Val 110/300, loss 0.8975, time 0.0773 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 111/300, loss 0.0002, time 0.6688
Val 111/300, loss 0.9273, time 0.0729 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 112/300, loss 0.0047, time 0.6146
Val 112/300, loss 1.0166, time 0.0743 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 113/300, loss 0.0232, time 0.6302
Val 113/300, loss 2.1042, time 0.1102 | acc 0.7797 | pre 0.7347 | recall 1.0000 | f1 0.8471
Train 114/300, loss 0.0188, time 0.6047
Val 114/300, loss 2.0976, time 0.0758 | acc 0.7627 | pre 0.7200 | recall 1.0000 | f1 0.8372
Train 115/300, loss 0.0193, time 0.6098
Val 115/300, loss 0.9720, time 0.0810 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 116/300, loss 0.1076, time 0.6528
Val 116/300, loss 1.0275, time 0.0754 | acc 0.9492 | pre 0.9231 | recall 1.0000 | f1 0.9600
Train 117/300, loss 0.0390, time 0.6337
Val 117/300, loss 1.2402, time 0.0775 | acc 0.8983 | pre 0.8571 | recall 1.0000 | f1 0.9231
Train 118/300, loss 0.0335, time 0.6260
Val 118/300, loss 1.2990, time 0.0753 | acc 0.7119 | pre 0.9130 | recall 0.5833 | f1 0.7119
Train 119/300, loss 0.0352, time 0.6277
Val 119/300, loss 0.7280, time 0.0761 | acc 0.8136 | pre 0.8788 | recall 0.8056 | f1 0.8406
Train 120/300, loss 0.0295, time 0.6664
Val 120/300, loss 0.6708, time 0.0741 | acc 0.8475 | pre 0.8649 | recall 0.8889 | f1 0.8767
Train 121/300, loss 0.0313, time 0.6238
Val 121/300, loss 0.6786, time 0.0763 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 122/300, loss 0.0594, time 0.6071
Val 122/300, loss 0.8732, time 0.1279 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 123/300, loss 0.0140, time 0.6080
Val 123/300, loss 0.8110, time 0.0754 | acc 0.8814 | pre 0.9394 | recall 0.8611 | f1 0.8986
Train 124/300, loss 0.0181, time 0.6708
Val 124/300, loss 0.5944, time 0.0711 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 125/300, loss 0.0075, time 0.6244
Val 125/300, loss 0.5980, time 0.0765 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 126/300, loss 0.0078, time 0.6640
Val 126/300, loss 0.6153, time 0.0740 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 127/300, loss 0.0046, time 0.6275
Val 127/300, loss 0.6075, time 0.0779 | acc 0.9153 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 128/300, loss 0.0093, time 0.6968
Val 128/300, loss 0.6482, time 0.0736 | acc 0.9322 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 129/300, loss 0.0017, time 0.6282
Val 129/300, loss 0.6865, time 0.0763 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 130/300, loss 0.0041, time 0.6753
Val 130/300, loss 0.7185, time 0.0737 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 131/300, loss 0.0012, time 0.6396
Val 131/300, loss 0.7762, time 0.0761 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 132/300, loss 0.0013, time 0.6408
Val 132/300, loss 0.8166, time 0.0755 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 133/300, loss 0.0005, time 0.6543
Val 133/300, loss 0.8456, time 0.0728 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 134/300, loss 0.0009, time 0.6220
Val 134/300, loss 0.8488, time 0.0746 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 135/300, loss 0.0016, time 0.6229
Val 135/300, loss 0.8301, time 0.0762 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 136/300, loss 0.0013, time 0.6430
Val 136/300, loss 0.7795, time 0.0762 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 137/300, loss 0.0007, time 0.6373
Val 137/300, loss 0.7944, time 0.0761 | acc 0.9153 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 138/300, loss 0.0004, time 0.6331
Val 138/300, loss 0.7826, time 0.0761 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 139/300, loss 0.0020, time 0.6308
Val 139/300, loss 0.7925, time 0.0759 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 140/300, loss 0.0005, time 0.6308
Val 140/300, loss 0.8208, time 0.0758 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 141/300, loss 0.0006, time 0.6310
Val 141/300, loss 0.8281, time 0.0761 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 142/300, loss 0.0005, time 0.6321
Val 142/300, loss 0.8387, time 0.0760 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 143/300, loss 0.0003, time 0.6291
Val 143/300, loss 0.8489, time 0.0732 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 144/300, loss 0.0004, time 0.6210
Val 144/300, loss 0.8371, time 0.0745 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 145/300, loss 0.0018, time 0.6276
Val 145/300, loss 0.7924, time 0.0742 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 146/300, loss 0.0007, time 0.6336
Val 146/300, loss 0.7969, time 0.0742 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 147/300, loss 0.0009, time 0.6224
Val 147/300, loss 0.7918, time 0.0742 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 148/300, loss 0.0002, time 0.6331
Val 148/300, loss 0.7801, time 0.0749 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 149/300, loss 0.0005, time 0.6231
Val 149/300, loss 0.7818, time 0.0747 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 150/300, loss 0.0013, time 0.6329
Val 150/300, loss 0.7938, time 0.0745 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 151/300, loss 0.0002, time 0.6210
Val 151/300, loss 0.7959, time 0.0751 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 152/300, loss 0.0004, time 0.6386
Val 152/300, loss 0.8218, time 0.0748 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 153/300, loss 0.0005, time 0.6261
Val 153/300, loss 0.8269, time 0.0745 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 154/300, loss 0.0002, time 0.6232
Val 154/300, loss 0.8302, time 0.0747 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 155/300, loss 0.0002, time 0.6328
Val 155/300, loss 0.8304, time 0.0746 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 156/300, loss 0.0002, time 0.6409
Val 156/300, loss 0.8359, time 0.0747 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 157/300, loss 0.0006, time 0.6254
Val 157/300, loss 0.8487, time 0.0747 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 158/300, loss 0.0001, time 0.6268
Val 158/300, loss 0.8588, time 0.0749 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 159/300, loss 0.0116, time 0.6306
Val 159/300, loss 0.9885, time 0.0753 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 160/300, loss 0.0194, time 0.6276
Val 160/300, loss 0.9453, time 0.0761 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 161/300, loss 0.0280, time 0.6476
Val 161/300, loss 1.0004, time 0.0754 | acc 0.8305 | pre 0.9062 | recall 0.8056 | f1 0.8529
Train 162/300, loss 0.0248, time 0.6275
Val 162/300, loss 0.9249, time 0.0754 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 163/300, loss 0.0079, time 0.6379
Val 163/300, loss 0.8576, time 0.0755 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 164/300, loss 0.0571, time 0.6295
Val 164/300, loss 0.9129, time 0.0757 | acc 0.9153 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 165/300, loss 0.0278, time 0.6499
Val 165/300, loss 1.4221, time 0.0748 | acc 0.8475 | pre 0.9355 | recall 0.8056 | f1 0.8657
Train 166/300, loss 0.0284, time 0.6325
Val 166/300, loss 1.0148, time 0.0758 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 167/300, loss 0.0193, time 0.6398
Val 167/300, loss 0.7877, time 0.0751 | acc 0.8983 | pre 0.9412 | recall 0.8889 | f1 0.9143
Train 168/300, loss 0.0102, time 0.6288
Val 168/300, loss 0.6971, time 0.0801 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 169/300, loss 0.0136, time 0.6281
Val 169/300, loss 0.9219, time 0.0745 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 170/300, loss 0.0235, time 0.6341
Val 170/300, loss 0.8740, time 0.0760 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 171/300, loss 0.0030, time 0.6362
Val 171/300, loss 0.7587, time 0.0762 | acc 0.9322 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 172/300, loss 0.0056, time 0.6361
Val 172/300, loss 0.7096, time 0.0760 | acc 0.9322 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 173/300, loss 0.0072, time 0.6450
Val 173/300, loss 0.7053, time 0.0776 | acc 0.8983 | pre 0.9412 | recall 0.8889 | f1 0.9143
Train 174/300, loss 0.0059, time 0.6374
Val 174/300, loss 0.6529, time 0.0762 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 175/300, loss 0.0013, time 0.6307
Val 175/300, loss 0.6611, time 0.0761 | acc 0.9322 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 176/300, loss 0.0007, time 0.6327
Val 176/300, loss 0.6665, time 0.0766 | acc 0.9153 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 177/300, loss 0.0008, time 0.6347
Val 177/300, loss 0.6861, time 0.0761 | acc 0.9153 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 178/300, loss 0.0013, time 0.6130
Val 178/300, loss 0.6858, time 0.0762 | acc 0.9322 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 179/300, loss 0.0006, time 0.6297
Val 179/300, loss 0.6970, time 0.0760 | acc 0.9322 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 180/300, loss 0.0010, time 0.6381
Val 180/300, loss 0.7036, time 0.0761 | acc 0.9322 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 181/300, loss 0.0019, time 0.6384
Val 181/300, loss 0.7084, time 0.0767 | acc 0.9322 | pre 0.9444 | recall 0.9444 | f1 0.9444
Train 182/300, loss 0.0002, time 0.6289
Val 182/300, loss 0.7218, time 0.0763 | acc 0.8983 | pre 0.9412 | recall 0.8889 | f1 0.9143
Train 183/300, loss 0.0008, time 0.6511
Val 183/300, loss 0.7161, time 0.0764 | acc 0.9153 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 184/300, loss 0.0007, time 0.6171
Val 184/300, loss 0.7119, time 0.0763 | acc 0.9153 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 185/300, loss 0.0002, time 0.5467
Val 185/300, loss 0.7152, time 0.0745 | acc 0.9153 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 186/300, loss 0.0005, time 0.5475
Val 186/300, loss 0.7094, time 0.0743 | acc 0.9322 | pre 0.9444 | recall 0.9444 | f1 0.9444
Train 187/300, loss 0.0002, time 0.5475
Val 187/300, loss 0.6994, time 0.0744 | acc 0.9322 | pre 0.9444 | recall 0.9444 | f1 0.9444
Train 188/300, loss 0.0005, time 0.5349
Val 188/300, loss 0.7216, time 0.0742 | acc 0.9322 | pre 0.9444 | recall 0.9444 | f1 0.9444
Train 189/300, loss 0.0004, time 0.5409
Val 189/300, loss 0.7172, time 0.0751 | acc 0.9322 | pre 0.9444 | recall 0.9444 | f1 0.9444
Train 190/300, loss 0.0003, time 0.6267
Val 190/300, loss 0.7159, time 0.0724 | acc 0.9322 | pre 0.9444 | recall 0.9444 | f1 0.9444
Train 191/300, loss 0.0001, time 0.5398
Val 191/300, loss 0.7260, time 0.0744 | acc 0.9153 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 192/300, loss 0.0002, time 0.5651
Val 192/300, loss 0.7387, time 0.1485 | acc 0.9153 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 193/300, loss 0.0063, time 0.6005
Val 193/300, loss 0.8839, time 0.0757 | acc 0.8475 | pre 0.9355 | recall 0.8056 | f1 0.8657
Train 194/300, loss 0.0836, time 0.6370
Val 194/300, loss 1.4425, time 0.0817 | acc 0.8136 | pre 0.9310 | recall 0.7500 | f1 0.8308
Train 195/300, loss 0.0969, time 0.6675
Val 195/300, loss 0.7796, time 0.0749 | acc 0.9153 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 196/300, loss 0.0260, time 0.6200
Val 196/300, loss 0.7505, time 0.0767 | acc 0.8983 | pre 0.8947 | recall 0.9444 | f1 0.9189
Train 197/300, loss 0.0213, time 0.6574
Val 197/300, loss 0.5815, time 0.0759 | acc 0.9153 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 198/300, loss 0.0036, time 0.6351
Val 198/300, loss 0.5900, time 0.0774 | acc 0.9153 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 199/300, loss 0.0101, time 0.7088
Val 199/300, loss 0.6849, time 0.0758 | acc 0.9153 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 200/300, loss 0.0147, time 0.6477
Val 200/300, loss 0.8905, time 0.0772 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 201/300, loss 0.0097, time 0.6514
Val 201/300, loss 0.9785, time 0.0748 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 202/300, loss 0.0026, time 0.6092
Val 202/300, loss 0.9823, time 0.0751 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 203/300, loss 0.0054, time 0.6260
Val 203/300, loss 1.0297, time 0.0756 | acc 0.9153 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 204/300, loss 0.0170, time 0.6344
Val 204/300, loss 0.9284, time 0.0773 | acc 0.9322 | pre 0.9444 | recall 0.9444 | f1 0.9444
Train 205/300, loss 0.0024, time 0.6223
Val 205/300, loss 0.9060, time 0.0755 | acc 0.9153 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 206/300, loss 0.0008, time 0.6278
Val 206/300, loss 0.9860, time 0.0774 | acc 0.9153 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 207/300, loss 0.0052, time 0.6757
Val 207/300, loss 0.9619, time 0.0741 | acc 0.9153 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 208/300, loss 0.0016, time 0.6282
Val 208/300, loss 0.9255, time 0.0767 | acc 0.8983 | pre 0.9412 | recall 0.8889 | f1 0.9143
Train 209/300, loss 0.0009, time 0.6775
Val 209/300, loss 0.9196, time 0.0734 | acc 0.8983 | pre 0.9412 | recall 0.8889 | f1 0.9143
Train 210/300, loss 0.0010, time 0.6334
Val 210/300, loss 0.9218, time 0.0771 | acc 0.9153 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 211/300, loss 0.0033, time 0.6280
Val 211/300, loss 0.9269, time 0.0755 | acc 0.8983 | pre 0.9412 | recall 0.8889 | f1 0.9143
Train 212/300, loss 0.0007, time 0.6347
Val 212/300, loss 0.9576, time 0.0773 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 213/300, loss 0.0023, time 0.6446
Val 213/300, loss 0.9853, time 0.0760 | acc 0.8983 | pre 0.9412 | recall 0.8889 | f1 0.9143
Train 214/300, loss 0.0006, time 0.6305
Val 214/300, loss 1.0375, time 0.0771 | acc 0.9153 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 215/300, loss 0.0030, time 0.7347
Val 215/300, loss 1.0190, time 0.0739 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 216/300, loss 0.0004, time 0.6363
Val 216/300, loss 1.0502, time 0.0774 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 217/300, loss 0.0007, time 0.6461
Val 217/300, loss 1.1090, time 0.0773 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 218/300, loss 0.0038, time 0.6405
Val 218/300, loss 1.1483, time 0.0773 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 219/300, loss 0.0003, time 0.6405
Val 219/300, loss 1.1862, time 0.0774 | acc 0.8814 | pre 0.9394 | recall 0.8611 | f1 0.8986
Train 220/300, loss 0.0010, time 0.6377
Val 220/300, loss 1.2176, time 0.0773 | acc 0.8983 | pre 0.9412 | recall 0.8889 | f1 0.9143
Train 221/300, loss 0.0010, time 0.6418
Val 221/300, loss 1.1902, time 0.0772 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 222/300, loss 0.0016, time 0.6404
Val 222/300, loss 1.1593, time 0.0774 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 223/300, loss 0.0007, time 0.6472
Val 223/300, loss 1.1676, time 0.0771 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 224/300, loss 0.0001, time 0.6291
Val 224/300, loss 1.1783, time 0.0771 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 225/300, loss 0.0015, time 0.6573
Val 225/300, loss 1.2121, time 0.0772 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 226/300, loss 0.0017, time 0.6353
Val 226/300, loss 1.2174, time 0.0772 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 227/300, loss 0.0008, time 0.6442
Val 227/300, loss 1.0519, time 0.0771 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 228/300, loss 0.0177, time 0.6472
Val 228/300, loss 0.9659, time 0.0772 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 229/300, loss 0.0098, time 0.6392
Val 229/300, loss 1.6121, time 0.0772 | acc 0.8475 | pre 0.9355 | recall 0.8056 | f1 0.8657
Train 230/300, loss 0.0198, time 0.6578
Val 230/300, loss 1.1741, time 0.0773 | acc 0.8983 | pre 0.9412 | recall 0.8889 | f1 0.9143
Train 231/300, loss 0.0024, time 0.6436
Val 231/300, loss 1.1616, time 0.0769 | acc 0.9322 | pre 0.9444 | recall 0.9444 | f1 0.9444
Train 232/300, loss 0.0011, time 0.6553
Val 232/300, loss 1.1533, time 0.0769 | acc 0.9153 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 233/300, loss 0.0227, time 0.6403
Val 233/300, loss 1.3511, time 0.0787 | acc 0.8475 | pre 0.9355 | recall 0.8056 | f1 0.8657
Train 234/300, loss 0.0131, time 0.6363
Val 234/300, loss 1.8046, time 0.0769 | acc 0.8136 | pre 0.9310 | recall 0.7500 | f1 0.8308
Train 235/300, loss 0.0129, time 0.6412
Val 235/300, loss 1.5165, time 0.0768 | acc 0.8475 | pre 0.9355 | recall 0.8056 | f1 0.8657
Train 236/300, loss 0.0031, time 0.6416
Val 236/300, loss 1.2788, time 0.0769 | acc 0.7966 | pre 0.8750 | recall 0.7778 | f1 0.8235
Train 237/300, loss 0.0083, time 0.6379
Val 237/300, loss 1.2635, time 0.0769 | acc 0.8475 | pre 0.8857 | recall 0.8611 | f1 0.8732
Train 238/300, loss 0.0024, time 0.6350
Val 238/300, loss 1.3403, time 0.0772 | acc 0.8475 | pre 0.8857 | recall 0.8611 | f1 0.8732
Train 239/300, loss 0.0029, time 0.6353
Val 239/300, loss 1.3194, time 0.0770 | acc 0.8475 | pre 0.8857 | recall 0.8611 | f1 0.8732
Train 240/300, loss 0.0013, time 0.6330
Val 240/300, loss 1.2814, time 0.0767 | acc 0.8475 | pre 0.8857 | recall 0.8611 | f1 0.8732
Train 241/300, loss 0.0016, time 0.6468
Val 241/300, loss 1.2444, time 0.0769 | acc 0.8814 | pre 0.8919 | recall 0.9167 | f1 0.9041
Train 242/300, loss 0.0029, time 0.6382
Val 242/300, loss 1.1974, time 0.0768 | acc 0.8814 | pre 0.8919 | recall 0.9167 | f1 0.9041
Train 243/300, loss 0.0010, time 0.6320
Val 243/300, loss 1.1962, time 0.0771 | acc 0.8814 | pre 0.8919 | recall 0.9167 | f1 0.9041
Train 244/300, loss 0.0004, time 0.6579
Val 244/300, loss 1.2403, time 0.0791 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 245/300, loss 0.0004, time 0.6710
Val 245/300, loss 1.2372, time 0.0780 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 246/300, loss 0.0003, time 0.6542
Val 246/300, loss 1.2410, time 0.0838 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 247/300, loss 0.0022, time 0.6513
Val 247/300, loss 1.2978, time 0.0760 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 248/300, loss 0.0002, time 0.6387
Val 248/300, loss 1.3892, time 0.0768 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 249/300, loss 0.0019, time 0.6533
Val 249/300, loss 1.3691, time 0.0772 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 250/300, loss 0.0004, time 0.6401
Val 250/300, loss 1.3874, time 0.0770 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 251/300, loss 0.0002, time 0.6441
Val 251/300, loss 1.3959, time 0.0768 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 252/300, loss 0.0009, time 0.6251
Val 252/300, loss 1.4642, time 0.0766 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 253/300, loss 0.0008, time 0.6402
Val 253/300, loss 1.5006, time 0.0765 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 254/300, loss 0.0001, time 0.6354
Val 254/300, loss 1.4855, time 0.0766 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 255/300, loss 0.0001, time 0.6543
Val 255/300, loss 1.5097, time 0.0769 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 256/300, loss 0.0005, time 0.6558
Val 256/300, loss 1.4868, time 0.0769 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 257/300, loss 0.0001, time 0.6549
Val 257/300, loss 1.4782, time 0.0766 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 258/300, loss 0.0001, time 0.6395
Val 258/300, loss 1.4917, time 0.0770 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 259/300, loss 0.0001, time 0.6344
Val 259/300, loss 1.4875, time 0.0768 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 260/300, loss 0.0000, time 0.6441
Val 260/300, loss 1.4891, time 0.0770 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 261/300, loss 0.0000, time 0.6740
Val 261/300, loss 1.5213, time 0.0768 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 262/300, loss 0.0001, time 0.6411
Val 262/300, loss 1.5203, time 0.0771 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 263/300, loss 0.0004, time 0.6388
Val 263/300, loss 1.5088, time 0.0740 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 264/300, loss 0.0000, time 0.6237
Val 264/300, loss 1.4899, time 0.0754 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 265/300, loss 0.0001, time 0.6306
Val 265/300, loss 1.5053, time 0.0755 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 266/300, loss 0.0001, time 0.6359
Val 266/300, loss 1.5205, time 0.0769 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 267/300, loss 0.0001, time 0.6415
Val 267/300, loss 1.4870, time 0.0777 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 268/300, loss 0.0001, time 0.6357
Val 268/300, loss 1.4981, time 0.0758 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 269/300, loss 0.0001, time 0.6472
Val 269/300, loss 1.4625, time 0.0756 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 270/300, loss 0.0000, time 0.6397
Val 270/300, loss 1.4270, time 0.0751 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 271/300, loss 0.0001, time 0.6318
Val 271/300, loss 1.4607, time 0.0762 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 272/300, loss 0.0001, time 0.6326
Val 272/300, loss 1.4496, time 0.0755 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 273/300, loss 0.0002, time 0.6423
Val 273/300, loss 1.4524, time 0.1632 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 274/300, loss 0.0001, time 0.6023
Val 274/300, loss 1.4707, time 0.0763 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 275/300, loss 0.0001, time 0.6275
Val 275/300, loss 1.4713, time 0.1671 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 276/300, loss 0.0008, time 0.6115
Val 276/300, loss 1.4488, time 0.0757 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 277/300, loss 0.0005, time 0.6536
Val 277/300, loss 1.3268, time 0.1763 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 278/300, loss 0.0014, time 0.6630
Val 278/300, loss 1.3308, time 0.0773 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 279/300, loss 0.0000, time 0.7098
Val 279/300, loss 1.4433, time 0.0746 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 280/300, loss 0.0263, time 0.6213
Val 280/300, loss 1.5711, time 0.0767 | acc 0.8814 | pre 0.9394 | recall 0.8611 | f1 0.8986
Train 281/300, loss 0.0428, time 0.7127
Val 281/300, loss 3.7329, time 0.0726 | acc 0.6610 | pre 0.9444 | recall 0.4722 | f1 0.6296
Train 282/300, loss 0.1375, time 0.6274
Val 282/300, loss 2.0659, time 0.0743 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 283/300, loss 0.1320, time 0.6942
Val 283/300, loss 1.2930, time 0.0730 | acc 0.7797 | pre 0.7674 | recall 0.9167 | f1 0.8354
Train 284/300, loss 0.2024, time 0.6074
Val 284/300, loss 0.9125, time 0.0795 | acc 0.8644 | pre 0.8182 | recall 1.0000 | f1 0.9000
Train 285/300, loss 0.1315, time 0.7009
Val 285/300, loss 1.0929, time 0.0727 | acc 0.8644 | pre 0.8333 | recall 0.9722 | f1 0.8974
Train 286/300, loss 0.1487, time 0.6032
Val 286/300, loss 0.8866, time 0.0759 | acc 0.8475 | pre 0.8649 | recall 0.8889 | f1 0.8767
Train 287/300, loss 0.0873, time 0.6852
Val 287/300, loss 0.8634, time 0.0727 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 288/300, loss 0.0989, time 0.6113
Val 288/300, loss 0.8054, time 0.0761 | acc 0.8814 | pre 0.9394 | recall 0.8611 | f1 0.8986
Train 289/300, loss 0.0637, time 0.6325
Val 289/300, loss 0.6834, time 0.1690 | acc 0.9153 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 290/300, loss 0.0174, time 0.5857
Val 290/300, loss 0.7406, time 0.0758 | acc 0.8814 | pre 0.9394 | recall 0.8611 | f1 0.8986
Train 291/300, loss 0.0099, time 0.6360
Val 291/300, loss 0.8343, time 0.1670 | acc 0.8814 | pre 0.9394 | recall 0.8611 | f1 0.8986
Train 292/300, loss 0.0118, time 0.6180
Val 292/300, loss 0.8786, time 0.0756 | acc 0.8814 | pre 0.9394 | recall 0.8611 | f1 0.8986
Train 293/300, loss 0.0116, time 0.7235
Val 293/300, loss 0.8058, time 0.0730 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 294/300, loss 0.0146, time 0.6323
Val 294/300, loss 0.8205, time 0.0762 | acc 0.8983 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 295/300, loss 0.0218, time 0.6635
Val 295/300, loss 0.8317, time 0.0735 | acc 0.8983 | pre 0.9412 | recall 0.8889 | f1 0.9143
Train 296/300, loss 0.0302, time 0.6277
Val 296/300, loss 0.8900, time 0.0756 | acc 0.8644 | pre 0.8889 | recall 0.8889 | f1 0.8889
Train 297/300, loss 0.0165, time 0.7061
Val 297/300, loss 1.0204, time 0.0741 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 298/300, loss 0.0586, time 0.6228
Val 298/300, loss 1.0560, time 0.0758 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 299/300, loss 0.0289, time 0.6332
Val 299/300, loss 1.1130, time 0.0763 | acc 0.8305 | pre 0.9333 | recall 0.7778 | f1 0.8485
Train 300/300, loss 0.0139, time 0.6467
Val 300/300, loss 0.9473, time 0.0763 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
best epoch: 115 acc: 0.9492 | Precision: 0.9231 | recall 1.0000 | f1 0.9600
Total time: 214.6998
Fold 2 / 5
GraphTransformer(
(embedding): Linear(in_features=4096, out_features=256, bias=False)
(encoder): GraphTransformerEncoder(
(layers): ModuleList(
(0-2): 3 x TransformerEncoderLayer(
(self_attn): Attention()
(linear1): Linear(in_features=256, out_features=128, bias=True)
(dropout): Dropout(p=0.1, inplace=False)
(linear2): Linear(in_features=128, out_features=256, bias=True)
(norm1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(norm2): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(dropout1): Dropout(p=0.1, inplace=False)
(dropout2): Dropout(p=0.1, inplace=False)
)
)
)
(classifier): Sequential(
(0): Linear(in_features=256, out_features=256, bias=True)
(1): ReLU(inplace=True)
(2): Linear(in_features=256, out_features=2, bias=True)
)
)
Total number of parameters: 3096706
Extracting 2-hop subgraphs...
Done!
Extracting 2-hop subgraphs...
Done!
Training...
Train 1/300, loss 0.5028, time 0.6857
Val 1/300, loss 0.6580, time 0.0843 | acc 0.6102 | pre 0.6102 | recall 1.0000 | f1 0.7579
Train 2/300, loss 0.2778, time 0.6438
Val 2/300, loss 0.6376, time 0.0772 | acc 0.6102 | pre 0.6102 | recall 1.0000 | f1 0.7579
Train 3/300, loss 0.2569, time 0.6446
Val 3/300, loss 0.6188, time 0.0772 | acc 0.6102 | pre 0.6102 | recall 1.0000 | f1 0.7579
Train 4/300, loss 0.1702, time 0.6378
Val 4/300, loss 0.5776, time 0.0757 | acc 0.6780 | pre 0.6604 | recall 0.9722 | f1 0.7865
Train 5/300, loss 0.1615, time 0.6370
Val 5/300, loss 0.5264, time 0.0770 | acc 0.8475 | pre 0.8857 | recall 0.8611 | f1 0.8732
Train 6/300, loss 0.1419, time 0.6370
Val 6/300, loss 0.4659, time 0.0772 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 7/300, loss 0.1299, time 0.6202
Val 7/300, loss 0.4144, time 0.0768 | acc 0.7966 | pre 0.7727 | recall 0.9444 | f1 0.8500
Train 8/300, loss 0.0832, time 0.6396
Val 8/300, loss 0.3825, time 0.0769 | acc 0.8305 | pre 0.8250 | recall 0.9167 | f1 0.8684
Train 9/300, loss 0.0920, time 0.6323
Val 9/300, loss 0.3827, time 0.0770 | acc 0.8305 | pre 0.9062 | recall 0.8056 | f1 0.8529
Train 10/300, loss 0.0637, time 0.6311
Val 10/300, loss 0.4427, time 0.0771 | acc 0.8475 | pre 0.9355 | recall 0.8056 | f1 0.8657
Train 11/300, loss 0.0562, time 0.6190
Val 11/300, loss 0.6061, time 0.0769 | acc 0.7797 | pre 0.8485 | recall 0.7778 | f1 0.8116
Train 12/300, loss 0.0619, time 0.6364
Val 12/300, loss 0.5458, time 0.0769 | acc 0.8475 | pre 0.8649 | recall 0.8889 | f1 0.8767
Train 13/300, loss 0.0553, time 0.6198
Val 13/300, loss 0.4947, time 0.0769 | acc 0.8305 | pre 0.8611 | recall 0.8611 | f1 0.8611
Train 14/300, loss 0.0525, time 0.6312
Val 14/300, loss 0.6089, time 0.0768 | acc 0.7966 | pre 0.8333 | recall 0.8333 | f1 0.8333
Train 15/300, loss 0.0430, time 0.6360
Val 15/300, loss 0.7476, time 0.0766 | acc 0.8475 | pre 0.9355 | recall 0.8056 | f1 0.8657
Train 16/300, loss 0.0585, time 0.6271
Val 16/300, loss 0.7674, time 0.0765 | acc 0.8475 | pre 0.9355 | recall 0.8056 | f1 0.8657
Train 17/300, loss 0.0724, time 0.6256
Val 17/300, loss 0.7229, time 0.0763 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 18/300, loss 0.0828, time 0.6379
Val 18/300, loss 0.8662, time 0.0764 | acc 0.8305 | pre 0.9643 | recall 0.7500 | f1 0.8437
Train 19/300, loss 0.0522, time 0.6197
Val 19/300, loss 0.6191, time 0.0769 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 20/300, loss 0.0503, time 0.6355
Val 20/300, loss 0.7049, time 0.0771 | acc 0.8136 | pre 0.8788 | recall 0.8056 | f1 0.8406
Train 21/300, loss 0.0333, time 0.6459
Val 21/300, loss 0.8793, time 0.0770 | acc 0.8136 | pre 0.9310 | recall 0.7500 | f1 0.8308
Train 22/300, loss 0.0466, time 0.6463
Val 22/300, loss 0.7523, time 0.0771 | acc 0.8305 | pre 0.9333 | recall 0.7778 | f1 0.8485
Train 23/300, loss 0.0561, time 0.6479
Val 23/300, loss 0.6847, time 0.0771 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 24/300, loss 0.0325, time 0.6267
Val 24/300, loss 0.6128, time 0.0769 | acc 0.7966 | pre 0.9000 | recall 0.7500 | f1 0.8182
Train 25/300, loss 0.0627, time 0.6245
Val 25/300, loss 0.6543, time 0.0768 | acc 0.8136 | pre 0.9032 | recall 0.7778 | f1 0.8358
Train 26/300, loss 0.0545, time 0.6252
Val 26/300, loss 0.6199, time 0.0769 | acc 0.8305 | pre 0.8611 | recall 0.8611 | f1 0.8611
Train 27/300, loss 0.0343, time 0.6362
Val 27/300, loss 0.7037, time 0.0770 | acc 0.8305 | pre 0.8824 | recall 0.8333 | f1 0.8571
Train 28/300, loss 0.0386, time 0.6435
Val 28/300, loss 0.7984, time 0.0770 | acc 0.8305 | pre 0.9333 | recall 0.7778 | f1 0.8485
Train 29/300, loss 0.0636, time 0.6433
Val 29/300, loss 1.2486, time 0.0772 | acc 0.7627 | pre 0.9583 | recall 0.6389 | f1 0.7667
Train 30/300, loss 0.0459, time 0.6336
Val 30/300, loss 1.0474, time 0.0770 | acc 0.7797 | pre 0.9600 | recall 0.6667 | f1 0.7869
Train 31/300, loss 0.0234, time 0.6349
Val 31/300, loss 0.6574, time 0.0769 | acc 0.8136 | pre 0.8788 | recall 0.8056 | f1 0.8406
Train 32/300, loss 0.0398, time 0.6329
Val 32/300, loss 0.6229, time 0.0777 | acc 0.8475 | pre 0.8649 | recall 0.8889 | f1 0.8767
Train 33/300, loss 0.0349, time 0.6353
Val 33/300, loss 0.7358, time 0.0771 | acc 0.8305 | pre 0.9062 | recall 0.8056 | f1 0.8529
Train 34/300, loss 0.0254, time 0.6417
Val 34/300, loss 0.8642, time 0.0773 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 35/300, loss 0.0153, time 0.6542
Val 35/300, loss 0.9114, time 0.0771 | acc 0.8475 | pre 0.8857 | recall 0.8611 | f1 0.8732
Train 36/300, loss 0.0220, time 0.6382
Val 36/300, loss 1.1893, time 0.0779 | acc 0.7797 | pre 0.7674 | recall 0.9167 | f1 0.8354
Train 37/300, loss 0.0306, time 0.6402
Val 37/300, loss 1.3667, time 0.0770 | acc 0.7966 | pre 0.8529 | recall 0.8056 | f1 0.8286
Train 38/300, loss 0.0483, time 0.6246
Val 38/300, loss 1.4811, time 0.0777 | acc 0.7797 | pre 0.8710 | recall 0.7500 | f1 0.8060
Train 39/300, loss 0.0440, time 0.6304
Val 39/300, loss 1.0113, time 0.0769 | acc 0.8136 | pre 0.9032 | recall 0.7778 | f1 0.8358
Train 40/300, loss 0.0084, time 0.6243
Val 40/300, loss 0.8443, time 0.0777 | acc 0.8136 | pre 0.9032 | recall 0.7778 | f1 0.8358
Train 41/300, loss 0.0164, time 0.6336
Val 41/300, loss 0.9004, time 0.0769 | acc 0.8305 | pre 0.9333 | recall 0.7778 | f1 0.8485
Train 42/300, loss 0.0380, time 0.6379
Val 42/300, loss 0.8119, time 0.0780 | acc 0.8475 | pre 0.9355 | recall 0.8056 | f1 0.8657
Train 43/300, loss 0.0199, time 0.6340
Val 43/300, loss 0.7925, time 0.0771 | acc 0.8136 | pre 0.8788 | recall 0.8056 | f1 0.8406
Train 44/300, loss 0.0079, time 0.6191
Val 44/300, loss 0.8630, time 0.0772 | acc 0.8475 | pre 0.9355 | recall 0.8056 | f1 0.8657
Train 45/300, loss 0.0126, time 0.6278
Val 45/300, loss 0.7856, time 0.0766 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 46/300, loss 0.0068, time 0.6482
Val 46/300, loss 0.7869, time 0.0765 | acc 0.8305 | pre 0.8421 | recall 0.8889 | f1 0.8649
Train 47/300, loss 0.0087, time 0.6397
Val 47/300, loss 0.8197, time 0.0771 | acc 0.8305 | pre 0.8611 | recall 0.8611 | f1 0.8611
Train 48/300, loss 0.0051, time 0.6341
Val 48/300, loss 0.8540, time 0.0772 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 49/300, loss 0.0034, time 0.6486
Val 49/300, loss 0.8939, time 0.0773 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 50/300, loss 0.0070, time 0.6403
Val 50/300, loss 0.9566, time 0.0770 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 51/300, loss 0.0024, time 0.6338
Val 51/300, loss 1.0068, time 0.0770 | acc 0.8136 | pre 0.8571 | recall 0.8333 | f1 0.8451
Train 52/300, loss 0.0060, time 0.6328
Val 52/300, loss 1.0864, time 0.0772 | acc 0.8136 | pre 0.8788 | recall 0.8056 | f1 0.8406
Train 53/300, loss 0.0104, time 0.6508
Val 53/300, loss 1.0576, time 0.0833 | acc 0.8136 | pre 0.8788 | recall 0.8056 | f1 0.8406
Train 54/300, loss 0.0041, time 0.7141
Val 54/300, loss 1.0847, time 0.0756 | acc 0.7966 | pre 0.8750 | recall 0.7778 | f1 0.8235
Train 55/300, loss 0.0008, time 0.6227
Val 55/300, loss 1.1102, time 0.0781 | acc 0.7966 | pre 0.8750 | recall 0.7778 | f1 0.8235
Train 56/300, loss 0.0017, time 0.7056
Val 56/300, loss 1.0927, time 0.0759 | acc 0.7966 | pre 0.8750 | recall 0.7778 | f1 0.8235
Train 57/300, loss 0.0012, time 0.6558
Val 57/300, loss 1.1034, time 0.0781 | acc 0.7966 | pre 0.8750 | recall 0.7778 | f1 0.8235
Train 58/300, loss 0.0006, time 0.6661
Val 58/300, loss 1.1065, time 0.0754 | acc 0.8136 | pre 0.8788 | recall 0.8056 | f1 0.8406
Train 59/300, loss 0.0009, time 0.6663
Val 59/300, loss 1.0984, time 0.0770 | acc 0.8136 | pre 0.8788 | recall 0.8056 | f1 0.8406
Train 60/300, loss 0.0011, time 0.6793
Val 60/300, loss 1.1134, time 0.0771 | acc 0.7966 | pre 0.8750 | recall 0.7778 | f1 0.8235
Train 61/300, loss 0.0006, time 0.6451
Val 61/300, loss 1.1451, time 0.0788 | acc 0.7966 | pre 0.8750 | recall 0.7778 | f1 0.8235
Train 62/300, loss 0.0014, time 0.6918
Val 62/300, loss 1.1377, time 0.0758 | acc 0.8305 | pre 0.8824 | recall 0.8333 | f1 0.8571
Train 63/300, loss 0.0016, time 0.6226
Val 63/300, loss 1.1700, time 0.0774 | acc 0.7966 | pre 0.8529 | recall 0.8056 | f1 0.8286
Train 64/300, loss 0.0004, time 0.6683
Val 64/300, loss 1.2110, time 0.0754 | acc 0.7966 | pre 0.8750 | recall 0.7778 | f1 0.8235
Train 65/300, loss 0.0005, time 0.6514
Val 65/300, loss 1.1804, time 0.0780 | acc 0.8136 | pre 0.8788 | recall 0.8056 | f1 0.8406
Train 66/300, loss 0.0003, time 0.6694
Val 66/300, loss 1.1461, time 0.0760 | acc 0.8136 | pre 0.8788 | recall 0.8056 | f1 0.8406
Train 67/300, loss 0.0016, time 0.6397
Val 67/300, loss 1.1438, time 0.0793 | acc 0.8136 | pre 0.8788 | recall 0.8056 | f1 0.8406
Train 68/300, loss 0.0006, time 0.6862
Val 68/300, loss 1.1201, time 0.0757 | acc 0.8136 | pre 0.8788 | recall 0.8056 | f1 0.8406
Train 69/300, loss 0.0004, time 0.6297
Val 69/300, loss 1.1265, time 0.0778 | acc 0.8136 | pre 0.8788 | recall 0.8056 | f1 0.8406
Train 70/300, loss 0.0007, time 0.7105
Val 70/300, loss 1.1378, time 0.0759 | acc 0.8136 | pre 0.8788 | recall 0.8056 | f1 0.8406
Train 71/300, loss 0.0003, time 0.6154
Val 71/300, loss 1.1245, time 0.0762 | acc 0.8475 | pre 0.8857 | recall 0.8611 | f1 0.8732
Train 72/300, loss 0.0007, time 0.6947
Val 72/300, loss 1.1546, time 0.0756 | acc 0.8136 | pre 0.8788 | recall 0.8056 | f1 0.8406
Train 73/300, loss 0.0002, time 0.6487
Val 73/300, loss 1.1713, time 0.0776 | acc 0.8136 | pre 0.8788 | recall 0.8056 | f1 0.8406
Train 74/300, loss 0.0004, time 0.6206
Val 74/300, loss 1.1717, time 0.0773 | acc 0.8475 | pre 0.8857 | recall 0.8611 | f1 0.8732
Train 75/300, loss 0.0003, time 0.6373
Val 75/300, loss 1.1860, time 0.0779 | acc 0.8305 | pre 0.8611 | recall 0.8611 | f1 0.8611
Train 76/300, loss 0.0003, time 0.6868
Val 76/300, loss 1.2118, time 0.0742 | acc 0.8136 | pre 0.8788 | recall 0.8056 | f1 0.8406
Train 77/300, loss 0.0002, time 0.6608
Val 77/300, loss 1.2305, time 0.0784 | acc 0.8136 | pre 0.8788 | recall 0.8056 | f1 0.8406
Train 78/300, loss 0.0002, time 0.6594
Val 78/300, loss 1.2657, time 0.0747 | acc 0.7966 | pre 0.8750 | recall 0.7778 | f1 0.8235
Train 79/300, loss 0.0007, time 0.6091
Val 79/300, loss 1.3322, time 0.0772 | acc 0.7966 | pre 0.8750 | recall 0.7778 | f1 0.8235
Train 80/300, loss 0.0005, time 0.6285
Val 80/300, loss 1.3701, time 0.0781 | acc 0.7966 | pre 0.8750 | recall 0.7778 | f1 0.8235
Train 81/300, loss 0.0003, time 0.6347
Val 81/300, loss 1.4026, time 0.0772 | acc 0.7966 | pre 0.8750 | recall 0.7778 | f1 0.8235
Train 82/300, loss 0.0077, time 0.6398
Val 82/300, loss 1.3760, time 0.0779 | acc 0.8136 | pre 0.9032 | recall 0.7778 | f1 0.8358
Train 83/300, loss 0.0549, time 0.6403
Val 83/300, loss 1.7271, time 0.0778 | acc 0.7966 | pre 0.9286 | recall 0.7222 | f1 0.8125
Train 84/300, loss 0.0205, time 0.6358
Val 84/300, loss 0.8391, time 0.0780 | acc 0.8475 | pre 0.8649 | recall 0.8889 | f1 0.8767
Train 85/300, loss 0.0753, time 0.6478
Val 85/300, loss 1.0764, time 0.0782 | acc 0.7966 | pre 0.9000 | recall 0.7500 | f1 0.8182
Train 86/300, loss 0.0565, time 0.6422
Val 86/300, loss 1.3072, time 0.0780 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 87/300, loss 0.0776, time 0.6431
Val 87/300, loss 1.4456, time 0.0777 | acc 0.7966 | pre 0.8333 | recall 0.8333 | f1 0.8333
Train 88/300, loss 0.1505, time 0.6402
Val 88/300, loss 1.0351, time 0.0781 | acc 0.8136 | pre 0.8571 | recall 0.8333 | f1 0.8451
Train 89/300, loss 0.0889, time 0.6443
Val 89/300, loss 1.7659, time 0.0781 | acc 0.7458 | pre 0.9565 | recall 0.6111 | f1 0.7458
Train 90/300, loss 0.0748, time 0.6398
Val 90/300, loss 0.9977, time 0.0780 | acc 0.8305 | pre 0.8824 | recall 0.8333 | f1 0.8571
Train 91/300, loss 0.0329, time 0.6470
Val 91/300, loss 0.9915, time 0.0778 | acc 0.7966 | pre 0.8529 | recall 0.8056 | f1 0.8286
Train 92/300, loss 0.0271, time 0.6522
Val 92/300, loss 1.1049, time 0.0777 | acc 0.8136 | pre 0.8788 | recall 0.8056 | f1 0.8406
Train 93/300, loss 0.0431, time 0.6432
Val 93/300, loss 1.4419, time 0.0779 | acc 0.8305 | pre 0.9062 | recall 0.8056 | f1 0.8529
Train 94/300, loss 0.0372, time 0.6396
Val 94/300, loss 1.4158, time 0.0777 | acc 0.7797 | pre 0.8286 | recall 0.8056 | f1 0.8169
Train 95/300, loss 0.0084, time 0.6511
Val 95/300, loss 1.3845, time 0.0781 | acc 0.7966 | pre 0.8529 | recall 0.8056 | f1 0.8286
Train 96/300, loss 0.0059, time 0.6448
Val 96/300, loss 1.3602, time 0.0777 | acc 0.7966 | pre 0.8750 | recall 0.7778 | f1 0.8235
Train 97/300, loss 0.0046, time 0.6397
Val 97/300, loss 1.4415, time 0.0778 | acc 0.7627 | pre 0.8235 | recall 0.7778 | f1 0.8000
Train 98/300, loss 0.0011, time 0.6352
Val 98/300, loss 1.4427, time 0.0778 | acc 0.7797 | pre 0.8286 | recall 0.8056 | f1 0.8169
Train 99/300, loss 0.0030, time 0.6393
Val 99/300, loss 1.4638, time 0.0765 | acc 0.7627 | pre 0.8235 | recall 0.7778 | f1 0.8000
Train 100/300, loss 0.0008, time 0.6292
Val 100/300, loss 1.3901, time 0.0765 | acc 0.7797 | pre 0.8286 | recall 0.8056 | f1 0.8169
Train 101/300, loss 0.0013, time 0.6266
Val 101/300, loss 1.3772, time 0.0761 | acc 0.7797 | pre 0.8485 | recall 0.7778 | f1 0.8116
Train 102/300, loss 0.0009, time 0.6386
Val 102/300, loss 1.4197, time 0.0762 | acc 0.7797 | pre 0.8485 | recall 0.7778 | f1 0.8116
Train 103/300, loss 0.0012, time 0.6442
Val 103/300, loss 1.4605, time 0.0773 | acc 0.7797 | pre 0.8485 | recall 0.7778 | f1 0.8116
Train 104/300, loss 0.0036, time 0.6425
Val 104/300, loss 1.4655, time 0.0779 | acc 0.7966 | pre 0.8750 | recall 0.7778 | f1 0.8235
Train 105/300, loss 0.0019, time 0.6400
Val 105/300, loss 1.4003, time 0.0786 | acc 0.7966 | pre 0.8750 | recall 0.7778 | f1 0.8235
Train 106/300, loss 0.0004, time 0.6469
Val 106/300, loss 1.2717, time 0.0777 | acc 0.8136 | pre 0.8788 | recall 0.8056 | f1 0.8406
Train 107/300, loss 0.0007, time 0.6406
Val 107/300, loss 1.2078, time 0.0775 | acc 0.8305 | pre 0.8824 | recall 0.8333 | f1 0.8571
Train 108/300, loss 0.0043, time 0.6281
Val 108/300, loss 1.2097, time 0.0775 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 109/300, loss 0.0008, time 0.6416
Val 109/300, loss 1.2743, time 0.0774 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 110/300, loss 0.0006, time 0.6398
Val 110/300, loss 1.3177, time 0.0774 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 111/300, loss 0.0008, time 0.6418
Val 111/300, loss 1.3468, time 0.0776 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 112/300, loss 0.0012, time 0.6571
Val 112/300, loss 1.3379, time 0.0777 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 113/300, loss 0.0004, time 0.6495
Val 113/300, loss 1.3334, time 0.0775 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 114/300, loss 0.0075, time 0.6449
Val 114/300, loss 1.4257, time 0.0774 | acc 0.8136 | pre 0.8571 | recall 0.8333 | f1 0.8451
Train 115/300, loss 0.0158, time 0.6395
Val 115/300, loss 1.4562, time 0.0761 | acc 0.8475 | pre 0.8857 | recall 0.8611 | f1 0.8732
Train 116/300, loss 0.0382, time 0.6349
Val 116/300, loss 1.1217, time 0.0767 | acc 0.8475 | pre 0.8857 | recall 0.8611 | f1 0.8732
Train 117/300, loss 0.0443, time 0.6309
Val 117/300, loss 0.9651, time 0.0767 | acc 0.8136 | pre 0.8571 | recall 0.8333 | f1 0.8451
Train 118/300, loss 0.0206, time 0.6447
Val 118/300, loss 0.9056, time 0.0759 | acc 0.8136 | pre 0.8788 | recall 0.8056 | f1 0.8406
Train 119/300, loss 0.0075, time 0.6325
Val 119/300, loss 0.8993, time 0.0765 | acc 0.8136 | pre 0.8788 | recall 0.8056 | f1 0.8406
Train 120/300, loss 0.0071, time 0.6349
Val 120/300, loss 0.8416, time 0.0773 | acc 0.8136 | pre 0.8788 | recall 0.8056 | f1 0.8406
Train 121/300, loss 0.0047, time 0.6378
Val 121/300, loss 0.9064, time 0.0764 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 122/300, loss 0.0058, time 0.6424
Val 122/300, loss 0.9611, time 0.0769 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 123/300, loss 0.0028, time 0.6304
Val 123/300, loss 1.0084, time 0.0763 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 124/300, loss 0.0033, time 0.6294
Val 124/300, loss 1.0296, time 0.0771 | acc 0.8475 | pre 0.8857 | recall 0.8611 | f1 0.8732
Train 125/300, loss 0.0074, time 0.6463
Val 125/300, loss 0.9840, time 0.0763 | acc 0.8475 | pre 0.8857 | recall 0.8611 | f1 0.8732
Train 126/300, loss 0.0091, time 0.6279
Val 126/300, loss 0.9968, time 0.0768 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 127/300, loss 0.0024, time 0.6345
Val 127/300, loss 1.1925, time 0.0760 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 128/300, loss 0.0037, time 0.6401
Val 128/300, loss 1.3130, time 0.0797 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 129/300, loss 0.0058, time 0.6728
Val 129/300, loss 1.4744, time 0.0797 | acc 0.7627 | pre 0.8056 | recall 0.8056 | f1 0.8056
Train 130/300, loss 0.0084, time 0.6793
Val 130/300, loss 1.7604, time 0.0797 | acc 0.7797 | pre 0.8286 | recall 0.8056 | f1 0.8169
Train 131/300, loss 0.0274, time 0.6732
Val 131/300, loss 1.8462, time 0.0789 | acc 0.7966 | pre 0.8750 | recall 0.7778 | f1 0.8235
Train 132/300, loss 0.0975, time 0.6755
Val 132/300, loss 1.4527, time 0.0784 | acc 0.6949 | pre 0.8750 | recall 0.5833 | f1 0.7000
Train 133/300, loss 0.1466, time 0.6744
Val 133/300, loss 0.7188, time 0.0790 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 134/300, loss 0.0714, time 0.6697
Val 134/300, loss 1.0659, time 0.0789 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 135/300, loss 0.0524, time 0.6818
Val 135/300, loss 0.9676, time 0.0791 | acc 0.8136 | pre 0.8571 | recall 0.8333 | f1 0.8451
Train 136/300, loss 0.0328, time 0.6550
Val 136/300, loss 0.9523, time 0.0788 | acc 0.8305 | pre 0.8824 | recall 0.8333 | f1 0.8571
Train 137/300, loss 0.0329, time 0.6496
Val 137/300, loss 1.0786, time 0.0788 | acc 0.7966 | pre 0.8529 | recall 0.8056 | f1 0.8286
Train 138/300, loss 0.0131, time 0.6447
Val 138/300, loss 1.2164, time 0.0785 | acc 0.7966 | pre 0.8529 | recall 0.8056 | f1 0.8286
Train 139/300, loss 0.0045, time 0.6413
Val 139/300, loss 1.2015, time 0.0784 | acc 0.8305 | pre 0.9062 | recall 0.8056 | f1 0.8529
Train 140/300, loss 0.0041, time 0.6614
Val 140/300, loss 1.1886, time 0.0790 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 141/300, loss 0.0045, time 0.6634
Val 141/300, loss 1.2419, time 0.0798 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 142/300, loss 0.0227, time 0.7756
Val 142/300, loss 1.2368, time 0.0791 | acc 0.8136 | pre 0.8571 | recall 0.8333 | f1 0.8451
Train 143/300, loss 0.0124, time 0.6806
Val 143/300, loss 1.3499, time 0.0804 | acc 0.8136 | pre 0.8571 | recall 0.8333 | f1 0.8451
Train 144/300, loss 0.0132, time 0.7107
Val 144/300, loss 1.3940, time 0.0799 | acc 0.8136 | pre 0.8571 | recall 0.8333 | f1 0.8451
Train 145/300, loss 0.0094, time 0.6771
Val 145/300, loss 1.4203, time 0.0802 | acc 0.7966 | pre 0.8529 | recall 0.8056 | f1 0.8286
Train 146/300, loss 0.0300, time 0.7145
Val 146/300, loss 1.7222, time 0.0789 | acc 0.8305 | pre 0.9333 | recall 0.7778 | f1 0.8485
Train 147/300, loss 0.0055, time 0.6991
Val 147/300, loss 2.1782, time 0.0806 | acc 0.8136 | pre 0.9630 | recall 0.7222 | f1 0.8254
Train 148/300, loss 0.0035, time 0.6959
Val 148/300, loss 1.8186, time 0.0789 | acc 0.8305 | pre 0.9333 | recall 0.7778 | f1 0.8485
Train 149/300, loss 0.0017, time 0.6699
Val 149/300, loss 1.5431, time 0.0792 | acc 0.8475 | pre 0.9355 | recall 0.8056 | f1 0.8657
Train 150/300, loss 0.0039, time 0.6767
Val 150/300, loss 1.3545, time 0.0801 | acc 0.8305 | pre 0.8824 | recall 0.8333 | f1 0.8571
Train 151/300, loss 0.0139, time 0.6899
Val 151/300, loss 1.0958, time 0.0875 | acc 0.8136 | pre 0.8571 | recall 0.8333 | f1 0.8451
Train 152/300, loss 0.0368, time 0.8762
Val 152/300, loss 1.7305, time 0.1119 | acc 0.8305 | pre 0.9062 | recall 0.8056 | f1 0.8529
Train 153/300, loss 0.0047, time 0.7496
Val 153/300, loss 1.9072, time 0.0853 | acc 0.8305 | pre 0.9333 | recall 0.7778 | f1 0.8485
Train 154/300, loss 0.0551, time 0.7347
Val 154/300, loss 1.3763, time 0.0831 | acc 0.8305 | pre 0.8824 | recall 0.8333 | f1 0.8571
Train 155/300, loss 0.0047, time 0.6872
Val 155/300, loss 1.1303, time 0.1815 | acc 0.7797 | pre 0.8710 | recall 0.7500 | f1 0.8060
Train 156/300, loss 0.0510, time 0.5869
Val 156/300, loss 0.8179, time 0.0817 | acc 0.8305 | pre 0.8824 | recall 0.8333 | f1 0.8571
Train 157/300, loss 0.0245, time 0.6693
Val 157/300, loss 0.8498, time 0.1412 | acc 0.8305 | pre 0.9062 | recall 0.8056 | f1 0.8529
Train 158/300, loss 0.0072, time 0.6398
Val 158/300, loss 0.7371, time 0.0818 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 159/300, loss 0.0020, time 0.6127
Val 159/300, loss 0.7920, time 0.1781 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 160/300, loss 0.0011, time 0.5806
Val 160/300, loss 0.8399, time 0.0800 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 161/300, loss 0.0019, time 0.6479
Val 161/300, loss 0.8726, time 0.0783 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 162/300, loss 0.0019, time 0.6611
Val 162/300, loss 0.9015, time 0.0790 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 163/300, loss 0.0065, time 0.6674
Val 163/300, loss 0.9385, time 0.0797 | acc 0.8475 | pre 0.8857 | recall 0.8611 | f1 0.8732
Train 164/300, loss 0.0007, time 0.6503
Val 164/300, loss 0.9966, time 0.0790 | acc 0.8475 | pre 0.8857 | recall 0.8611 | f1 0.8732
Train 165/300, loss 0.0015, time 0.6673
Val 165/300, loss 1.0399, time 0.0791 | acc 0.8475 | pre 0.8857 | recall 0.8611 | f1 0.8732
Train 166/300, loss 0.0020, time 0.6585
Val 166/300, loss 1.0645, time 0.0783 | acc 0.8136 | pre 0.8571 | recall 0.8333 | f1 0.8451
Train 167/300, loss 0.0006, time 0.6655
Val 167/300, loss 1.0818, time 0.0797 | acc 0.8136 | pre 0.8571 | recall 0.8333 | f1 0.8451
Train 168/300, loss 0.0011, time 0.6582
Val 168/300, loss 1.1097, time 0.0783 | acc 0.8136 | pre 0.8571 | recall 0.8333 | f1 0.8451
Train 169/300, loss 0.0024, time 0.6798
Val 169/300, loss 1.1450, time 0.0799 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 170/300, loss 0.0144, time 0.6482
Val 170/300, loss 1.1175, time 0.0786 | acc 0.8305 | pre 0.8824 | recall 0.8333 | f1 0.8571
Train 171/300, loss 0.0073, time 0.6622
Val 171/300, loss 0.9656, time 0.0793 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 172/300, loss 0.0261, time 0.6727
Val 172/300, loss 0.9044, time 0.0787 | acc 0.8305 | pre 0.8824 | recall 0.8333 | f1 0.8571
Train 173/300, loss 0.0085, time 0.6719
Val 173/300, loss 0.9570, time 0.0789 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 174/300, loss 0.0035, time 0.6689
Val 174/300, loss 1.0165, time 0.0788 | acc 0.8305 | pre 0.9062 | recall 0.8056 | f1 0.8529
Train 175/300, loss 0.0010, time 0.6759
Val 175/300, loss 1.0887, time 0.0796 | acc 0.8305 | pre 0.9062 | recall 0.8056 | f1 0.8529
Train 176/300, loss 0.0015, time 0.6711
Val 176/300, loss 1.1378, time 0.0809 | acc 0.8305 | pre 0.9062 | recall 0.8056 | f1 0.8529
Train 177/300, loss 0.0091, time 0.6690
Val 177/300, loss 1.1755, time 0.0797 | acc 0.8136 | pre 0.8788 | recall 0.8056 | f1 0.8406
Train 178/300, loss 0.0050, time 0.6762
Val 178/300, loss 1.4955, time 0.0793 | acc 0.8305 | pre 0.9333 | recall 0.7778 | f1 0.8485
Train 179/300, loss 0.0042, time 0.6833
Val 179/300, loss 1.3621, time 0.0802 | acc 0.8305 | pre 0.9333 | recall 0.7778 | f1 0.8485
Train 180/300, loss 0.0171, time 0.6751
Val 180/300, loss 1.1722, time 0.0795 | acc 0.8305 | pre 0.9062 | recall 0.8056 | f1 0.8529
Train 181/300, loss 0.0031, time 0.6814
Val 181/300, loss 0.9267, time 0.0789 | acc 0.7627 | pre 0.7895 | recall 0.8333 | f1 0.8108
Train 182/300, loss 0.0191, time 0.6719
Val 182/300, loss 0.8153, time 0.0788 | acc 0.8305 | pre 0.8611 | recall 0.8611 | f1 0.8611
Train 183/300, loss 0.0021, time 0.6716
Val 183/300, loss 0.8350, time 0.0793 | acc 0.8475 | pre 0.8857 | recall 0.8611 | f1 0.8732
Train 184/300, loss 0.0167, time 0.6835
Val 184/300, loss 0.8832, time 0.0799 | acc 0.8305 | pre 0.8611 | recall 0.8611 | f1 0.8611
Train 185/300, loss 0.0027, time 0.6760
Val 185/300, loss 1.1800, time 0.0795 | acc 0.8136 | pre 0.8049 | recall 0.9167 | f1 0.8571
Train 186/300, loss 0.0016, time 0.6243
Val 186/300, loss 1.3012, time 0.0790 | acc 0.8136 | pre 0.8049 | recall 0.9167 | f1 0.8571
Train 187/300, loss 0.0044, time 0.6822
Val 187/300, loss 1.2966, time 0.0787 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 188/300, loss 0.0084, time 0.6823
Val 188/300, loss 1.2456, time 0.0788 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 189/300, loss 0.0150, time 0.6760
Val 189/300, loss 1.3649, time 0.0795 | acc 0.7797 | pre 0.8108 | recall 0.8333 | f1 0.8219
Train 190/300, loss 0.0101, time 0.6658
Val 190/300, loss 1.3073, time 0.0797 | acc 0.7288 | pre 0.7500 | recall 0.8333 | f1 0.7895
Train 191/300, loss 0.0384, time 0.6712
Val 191/300, loss 1.1319, time 0.0792 | acc 0.7797 | pre 0.8108 | recall 0.8333 | f1 0.8219
Train 192/300, loss 0.0352, time 0.6715
Val 192/300, loss 1.1679, time 0.0802 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 193/300, loss 0.0109, time 0.6649
Val 193/300, loss 1.3577, time 0.0792 | acc 0.8136 | pre 0.9032 | recall 0.7778 | f1 0.8358
Train 194/300, loss 0.0566, time 0.6668
Val 194/300, loss 1.4353, time 0.0789 | acc 0.8136 | pre 0.9032 | recall 0.7778 | f1 0.8358
Train 195/300, loss 0.0293, time 0.6713
Val 195/300, loss 1.7966, time 0.0792 | acc 0.8136 | pre 0.9032 | recall 0.7778 | f1 0.8358
Train 196/300, loss 0.0124, time 0.6694
Val 196/300, loss 2.1606, time 0.0794 | acc 0.7966 | pre 0.9615 | recall 0.6944 | f1 0.8065
Train 197/300, loss 0.0462, time 0.6628
Val 197/300, loss 1.6082, time 0.0782 | acc 0.7966 | pre 0.8750 | recall 0.7778 | f1 0.8235
Train 198/300, loss 0.0228, time 0.6647
Val 198/300, loss 1.9173, time 0.0791 | acc 0.8136 | pre 0.9310 | recall 0.7500 | f1 0.8308
Train 199/300, loss 0.0469, time 0.6717
Val 199/300, loss 1.7898, time 0.0800 | acc 0.7966 | pre 0.8750 | recall 0.7778 | f1 0.8235
Train 200/300, loss 0.0571, time 0.6691
Val 200/300, loss 1.4198, time 0.0789 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 201/300, loss 0.0420, time 0.6768
Val 201/300, loss 0.9981, time 0.0791 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 202/300, loss 0.0518, time 0.6565
Val 202/300, loss 1.0161, time 0.0791 | acc 0.8475 | pre 0.9355 | recall 0.8056 | f1 0.8657
Train 203/300, loss 0.0351, time 0.6902
Val 203/300, loss 1.0017, time 0.0795 | acc 0.8475 | pre 0.8857 | recall 0.8611 | f1 0.8732
Train 204/300, loss 0.0156, time 0.6833
Val 204/300, loss 1.2436, time 0.0794 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 205/300, loss 0.0118, time 0.6699
Val 205/300, loss 1.2424, time 0.0797 | acc 0.8475 | pre 0.8857 | recall 0.8611 | f1 0.8732
Train 206/300, loss 0.0037, time 0.6720
Val 206/300, loss 1.2450, time 0.0787 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 207/300, loss 0.0148, time 0.6684
Val 207/300, loss 1.2302, time 0.0787 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 208/300, loss 0.0280, time 0.6712
Val 208/300, loss 1.2737, time 0.0789 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 209/300, loss 0.0222, time 0.6771
Val 209/300, loss 1.2728, time 0.0790 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 210/300, loss 0.0055, time 0.6722
Val 210/300, loss 1.3617, time 0.0793 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 211/300, loss 0.0018, time 0.6841
Val 211/300, loss 1.4575, time 0.0793 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 212/300, loss 0.0037, time 0.6822
Val 212/300, loss 1.4406, time 0.0789 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 213/300, loss 0.0017, time 0.6705
Val 213/300, loss 1.3896, time 0.0790 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 214/300, loss 0.0018, time 0.6664
Val 214/300, loss 1.4320, time 0.0790 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 215/300, loss 0.0012, time 0.7160
Val 215/300, loss 1.4724, time 0.0788 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 216/300, loss 0.0007, time 0.6772
Val 216/300, loss 1.4766, time 0.0801 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 217/300, loss 0.0020, time 0.6642
Val 217/300, loss 1.5052, time 0.0801 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 218/300, loss 0.0002, time 0.6567
Val 218/300, loss 1.5126, time 0.0804 | acc 0.8305 | pre 0.8824 | recall 0.8333 | f1 0.8571
Train 219/300, loss 0.0009, time 0.6468
Val 219/300, loss 1.5463, time 0.0798 | acc 0.8305 | pre 0.8824 | recall 0.8333 | f1 0.8571
Train 220/300, loss 0.0027, time 0.6468
Val 220/300, loss 1.6183, time 0.0759 | acc 0.8305 | pre 0.8824 | recall 0.8333 | f1 0.8571
Train 221/300, loss 0.0004, time 0.6989
Val 221/300, loss 1.6490, time 0.0803 | acc 0.8305 | pre 0.8824 | recall 0.8333 | f1 0.8571
Train 222/300, loss 0.0003, time 0.6502
Val 222/300, loss 1.6518, time 0.0787 | acc 0.8305 | pre 0.8824 | recall 0.8333 | f1 0.8571
Train 223/300, loss 0.0018, time 0.6800
Val 223/300, loss 1.6755, time 0.0759 | acc 0.8305 | pre 0.8824 | recall 0.8333 | f1 0.8571
Train 224/300, loss 0.0007, time 0.6223
Val 224/300, loss 1.7019, time 0.0786 | acc 0.8305 | pre 0.8824 | recall 0.8333 | f1 0.8571
Train 225/300, loss 0.0072, time 0.6594
Val 225/300, loss 1.6449, time 0.0759 | acc 0.8305 | pre 0.8824 | recall 0.8333 | f1 0.8571
Train 226/300, loss 0.0151, time 0.5465
Val 226/300, loss 1.7522, time 0.0765 | acc 0.8305 | pre 0.8824 | recall 0.8333 | f1 0.8571
Train 227/300, loss 0.0004, time 0.6134
Val 227/300, loss 1.8438, time 0.1610 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 228/300, loss 0.0009, time 0.6174
Val 228/300, loss 1.7831, time 0.0766 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 229/300, loss 0.0123, time 0.6345
Val 229/300, loss 1.7257, time 0.0828 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 230/300, loss 0.0008, time 0.6089
Val 230/300, loss 1.7096, time 0.0769 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 231/300, loss 0.0011, time 0.6181
Val 231/300, loss 1.7499, time 0.0849 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 232/300, loss 0.0055, time 0.6855
Val 232/300, loss 1.6672, time 0.0789 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 233/300, loss 0.0004, time 0.6361
Val 233/300, loss 1.3537, time 0.0781 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 234/300, loss 0.0066, time 0.6429
Val 234/300, loss 1.4811, time 0.0751 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 235/300, loss 0.0038, time 0.6525
Val 235/300, loss 1.5191, time 0.0778 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 236/300, loss 0.0012, time 0.6830
Val 236/300, loss 1.4958, time 0.0742 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 237/300, loss 0.0019, time 0.6255
Val 237/300, loss 1.5136, time 0.0772 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 238/300, loss 0.0023, time 0.6996
Val 238/300, loss 1.5536, time 0.0749 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 239/300, loss 0.0004, time 0.6204
Val 239/300, loss 1.5091, time 0.0763 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 240/300, loss 0.0008, time 0.6633
Val 240/300, loss 1.5566, time 0.0766 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 241/300, loss 0.0005, time 0.6373
Val 241/300, loss 1.5026, time 0.0780 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 242/300, loss 0.0051, time 0.6409
Val 242/300, loss 1.5745, time 0.0780 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 243/300, loss 0.0023, time 0.6424
Val 243/300, loss 1.6285, time 0.0784 | acc 0.8136 | pre 0.8571 | recall 0.8333 | f1 0.8451
Train 244/300, loss 0.0026, time 0.6288
Val 244/300, loss 1.8602, time 0.0784 | acc 0.8305 | pre 0.8824 | recall 0.8333 | f1 0.8571
Train 245/300, loss 0.0044, time 0.6351
Val 245/300, loss 1.9537, time 0.0782 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 246/300, loss 0.0016, time 0.6538
Val 246/300, loss 2.0068, time 0.0769 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 247/300, loss 0.0048, time 0.6358
Val 247/300, loss 1.9295, time 0.0879 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 248/300, loss 0.0063, time 0.6505
Val 248/300, loss 1.8390, time 0.0761 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 249/300, loss 0.0186, time 0.6140
Val 249/300, loss 1.9641, time 0.0765 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 250/300, loss 0.0583, time 0.6221
Val 250/300, loss 2.8090, time 0.0775 | acc 0.7797 | pre 0.8710 | recall 0.7500 | f1 0.8060
Train 251/300, loss 0.0566, time 0.6230
Val 251/300, loss 2.8482, time 0.0779 | acc 0.7966 | pre 0.9286 | recall 0.7222 | f1 0.8125
Train 252/300, loss 0.0277, time 0.6513
Val 252/300, loss 2.2722, time 0.0786 | acc 0.7966 | pre 0.9286 | recall 0.7222 | f1 0.8125
Train 253/300, loss 0.0518, time 0.6466
Val 253/300, loss 1.3717, time 0.0788 | acc 0.8136 | pre 0.9032 | recall 0.7778 | f1 0.8358
Train 254/300, loss 0.0263, time 0.6334
Val 254/300, loss 1.0566, time 0.0785 | acc 0.8475 | pre 0.8857 | recall 0.8611 | f1 0.8732
Train 255/300, loss 0.0301, time 0.6396
Val 255/300, loss 0.9327, time 0.0787 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 256/300, loss 0.0215, time 0.6424
Val 256/300, loss 1.0078, time 0.0785 | acc 0.8305 | pre 0.9333 | recall 0.7778 | f1 0.8485
Train 257/300, loss 0.0407, time 0.6268
Val 257/300, loss 1.3266, time 0.0786 | acc 0.8136 | pre 0.9032 | recall 0.7778 | f1 0.8358
Train 258/300, loss 0.0435, time 0.6292
Val 258/300, loss 1.6346, time 0.0787 | acc 0.7966 | pre 0.9286 | recall 0.7222 | f1 0.8125
Train 259/300, loss 0.0367, time 0.6385
Val 259/300, loss 1.1495, time 0.0787 | acc 0.8305 | pre 0.9643 | recall 0.7500 | f1 0.8437
Train 260/300, loss 0.0828, time 0.6334
Val 260/300, loss 1.1181, time 0.0783 | acc 0.7966 | pre 0.8750 | recall 0.7778 | f1 0.8235
Train 261/300, loss 0.0435, time 0.6319
Val 261/300, loss 0.9845, time 0.0783 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 262/300, loss 0.0150, time 0.6335
Val 262/300, loss 0.9381, time 0.0785 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 263/300, loss 0.0249, time 0.6417
Val 263/300, loss 0.8446, time 0.0783 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 264/300, loss 0.0059, time 0.6297
Val 264/300, loss 0.8575, time 0.0783 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 265/300, loss 0.0216, time 0.6268
Val 265/300, loss 0.7671, time 0.0790 | acc 0.8305 | pre 0.8611 | recall 0.8611 | f1 0.8611
Train 266/300, loss 0.0118, time 0.6518
Val 266/300, loss 0.6508, time 0.0802 | acc 0.8475 | pre 0.8649 | recall 0.8889 | f1 0.8767
Train 267/300, loss 0.0043, time 0.6522
Val 267/300, loss 0.6743, time 0.0787 | acc 0.8475 | pre 0.8649 | recall 0.8889 | f1 0.8767
Train 268/300, loss 0.0036, time 0.6188
Val 268/300, loss 0.7244, time 0.0787 | acc 0.8305 | pre 0.8611 | recall 0.8611 | f1 0.8611
Train 269/300, loss 0.0030, time 0.6169
Val 269/300, loss 0.7919, time 0.0780 | acc 0.8305 | pre 0.8611 | recall 0.8611 | f1 0.8611
Train 270/300, loss 0.0022, time 0.6342
Val 270/300, loss 0.8136, time 0.0792 | acc 0.8305 | pre 0.8824 | recall 0.8333 | f1 0.8571
Train 271/300, loss 0.0006, time 0.6358
Val 271/300, loss 0.8314, time 0.0757 | acc 0.8475 | pre 0.8857 | recall 0.8611 | f1 0.8732
Train 272/300, loss 0.0013, time 0.6191
Val 272/300, loss 0.9060, time 0.0766 | acc 0.8475 | pre 0.8857 | recall 0.8611 | f1 0.8732
Train 273/300, loss 0.0026, time 0.6532
Val 273/300, loss 1.1998, time 0.0768 | acc 0.7966 | pre 0.7857 | recall 0.9167 | f1 0.8462
Train 274/300, loss 0.0108, time 0.6384
Val 274/300, loss 4.8103, time 0.0768 | acc 0.5932 | pre 0.6071 | recall 0.9444 | f1 0.7391
Train 275/300, loss 0.0444, time 0.6234
Val 275/300, loss 2.4050, time 0.0771 | acc 0.6949 | pre 0.6957 | recall 0.8889 | f1 0.7805
Train 276/300, loss 0.0140, time 0.6216
Val 276/300, loss 1.2552, time 0.0771 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 277/300, loss 0.0254, time 0.6364
Val 277/300, loss 2.0863, time 0.0774 | acc 0.7627 | pre 0.7895 | recall 0.8333 | f1 0.8108
Train 278/300, loss 0.0228, time 0.6287
Val 278/300, loss 2.5625, time 0.0772 | acc 0.8136 | pre 0.8788 | recall 0.8056 | f1 0.8406
Train 279/300, loss 0.0158, time 0.6275
Val 279/300, loss 2.7723, time 0.0770 | acc 0.8305 | pre 0.9062 | recall 0.8056 | f1 0.8529
Train 280/300, loss 0.0252, time 0.6133
Val 280/300, loss 2.9768, time 0.0772 | acc 0.7966 | pre 0.9000 | recall 0.7500 | f1 0.8182
Train 281/300, loss 0.0054, time 0.6323
Val 281/300, loss 2.8935, time 0.0769 | acc 0.8305 | pre 0.9062 | recall 0.8056 | f1 0.8529
Train 282/300, loss 0.0307, time 0.6185
Val 282/300, loss 2.0083, time 0.0769 | acc 0.8475 | pre 0.9355 | recall 0.8056 | f1 0.8657
Train 283/300, loss 0.0565, time 0.6268
Val 283/300, loss 1.2381, time 0.0768 | acc 0.8305 | pre 0.9062 | recall 0.8056 | f1 0.8529
Train 284/300, loss 0.0474, time 0.6328
Val 284/300, loss 1.2069, time 0.0769 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 285/300, loss 0.0324, time 0.6346
Val 285/300, loss 1.4788, time 0.0768 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 286/300, loss 0.0194, time 0.6257
Val 286/300, loss 1.7395, time 0.0766 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 287/300, loss 0.0119, time 0.6307
Val 287/300, loss 1.7270, time 0.0785 | acc 0.8475 | pre 0.9655 | recall 0.7778 | f1 0.8615
Train 288/300, loss 0.0162, time 0.5786
Val 288/300, loss 1.7123, time 0.0776 | acc 0.8644 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 289/300, loss 0.0032, time 0.6090
Val 289/300, loss 1.7638, time 0.0775 | acc 0.8136 | pre 0.9032 | recall 0.7778 | f1 0.8358
Train 290/300, loss 0.0278, time 0.6223
Val 290/300, loss 1.7072, time 0.0784 | acc 0.7966 | pre 0.8750 | recall 0.7778 | f1 0.8235
Train 291/300, loss 0.0709, time 0.6927
Val 291/300, loss 1.9367, time 0.0933 | acc 0.7797 | pre 0.8286 | recall 0.8056 | f1 0.8169
Train 292/300, loss 0.1042, time 0.6508
Val 292/300, loss 1.3751, time 0.0778 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 293/300, loss 0.0248, time 0.6386
Val 293/300, loss 0.9795, time 0.0786 | acc 0.8475 | pre 0.8649 | recall 0.8889 | f1 0.8767
Train 294/300, loss 0.0438, time 0.6529
Val 294/300, loss 1.0491, time 0.0780 | acc 0.8814 | pre 1.0000 | recall 0.8056 | f1 0.8923
Train 295/300, loss 0.0377, time 0.6218
Val 295/300, loss 1.2900, time 0.0790 | acc 0.8644 | pre 0.9667 | recall 0.8056 | f1 0.8788
Train 296/300, loss 0.0318, time 0.6514
Val 296/300, loss 1.0938, time 0.0791 | acc 0.8644 | pre 0.8889 | recall 0.8889 | f1 0.8889
Train 297/300, loss 0.0170, time 0.6419
Val 297/300, loss 1.0561, time 0.0788 | acc 0.8644 | pre 0.8889 | recall 0.8889 | f1 0.8889
Train 298/300, loss 0.0073, time 0.6445
Val 298/300, loss 0.9913, time 0.0790 | acc 0.8814 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 299/300, loss 0.0053, time 0.7056
Val 299/300, loss 1.0371, time 0.0745 | acc 0.8644 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 300/300, loss 0.0030, time 0.6072
Val 300/300, loss 1.0560, time 0.0766 | acc 0.8983 | pre 0.9688 | recall 0.8611 | f1 0.9118
best epoch: 299 acc: 0.8983 | Precision: 0.9688 | recall 0.8611 | f1 0.9118
Total time: 219.2558
Fold 3 / 5
GraphTransformer(
(embedding): Linear(in_features=4096, out_features=256, bias=False)
(encoder): GraphTransformerEncoder(
(layers): ModuleList(
(0-2): 3 x TransformerEncoderLayer(
(self_attn): Attention()
(linear1): Linear(in_features=256, out_features=128, bias=True)
(dropout): Dropout(p=0.1, inplace=False)
(linear2): Linear(in_features=128, out_features=256, bias=True)
(norm1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(norm2): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(dropout1): Dropout(p=0.1, inplace=False)
(dropout2): Dropout(p=0.1, inplace=False)
)
)
)
(classifier): Sequential(
(0): Linear(in_features=256, out_features=256, bias=True)
(1): ReLU(inplace=True)
(2): Linear(in_features=256, out_features=2, bias=True)
)
)
Total number of parameters: 3096706
Extracting 2-hop subgraphs...
Done!
Extracting 2-hop subgraphs...
Done!
Training...
Train 1/300, loss 0.5005, time 0.6455
Val 1/300, loss 0.6662, time 0.0764 | acc 0.6780 | pre 0.6604 | recall 0.9722 | f1 0.7865
Train 2/300, loss 0.2702, time 0.6247
Val 2/300, loss 0.6464, time 0.0754 | acc 0.6610 | pre 0.6429 | recall 1.0000 | f1 0.7826
Train 3/300, loss 0.2198, time 0.6432
Val 3/300, loss 0.6192, time 0.0763 | acc 0.7288 | pre 0.7174 | recall 0.9167 | f1 0.8049
Train 4/300, loss 0.1788, time 0.6776
Val 4/300, loss 0.5698, time 0.0752 | acc 0.7797 | pre 0.7447 | recall 0.9722 | f1 0.8434
Train 5/300, loss 0.1437, time 0.6344
Val 5/300, loss 0.5202, time 0.0763 | acc 0.7627 | pre 0.7500 | recall 0.9167 | f1 0.8250
Train 6/300, loss 0.1110, time 0.6867
Val 6/300, loss 0.4680, time 0.0752 | acc 0.7458 | pre 0.7561 | recall 0.8611 | f1 0.8052
Train 7/300, loss 0.0823, time 0.6421
Val 7/300, loss 0.4065, time 0.0779 | acc 0.7458 | pre 0.7692 | recall 0.8333 | f1 0.8000
Train 8/300, loss 0.0637, time 0.6388
Val 8/300, loss 0.3854, time 0.0767 | acc 0.7458 | pre 0.7692 | recall 0.8333 | f1 0.8000
Train 9/300, loss 0.0410, time 0.6301
Val 9/300, loss 0.4925, time 0.0780 | acc 0.7627 | pre 0.7895 | recall 0.8333 | f1 0.8108
Train 10/300, loss 0.0364, time 0.6611
Val 10/300, loss 0.6352, time 0.0737 | acc 0.7797 | pre 0.8286 | recall 0.8056 | f1 0.8169
Train 11/300, loss 0.0297, time 0.6458
Val 11/300, loss 0.7535, time 0.0779 | acc 0.7797 | pre 0.8286 | recall 0.8056 | f1 0.8169
Train 12/300, loss 0.0238, time 0.6878
Val 12/300, loss 0.8358, time 0.0737 | acc 0.7966 | pre 0.8333 | recall 0.8333 | f1 0.8333
Train 13/300, loss 0.0310, time 0.6363
Val 13/300, loss 0.8576, time 0.0774 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 14/300, loss 0.0197, time 0.6529
Val 14/300, loss 0.9564, time 0.0716 | acc 0.7966 | pre 0.7857 | recall 0.9167 | f1 0.8462
Train 15/300, loss 0.0246, time 0.5401
Val 15/300, loss 1.0848, time 0.0754 | acc 0.7797 | pre 0.7674 | recall 0.9167 | f1 0.8354
Train 16/300, loss 0.0397, time 0.5952
Val 16/300, loss 1.2327, time 0.0730 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 17/300, loss 0.0496, time 0.6236
Val 17/300, loss 0.8553, time 0.0754 | acc 0.7966 | pre 0.8529 | recall 0.8056 | f1 0.8286
Train 18/300, loss 0.0496, time 0.6955
Val 18/300, loss 1.0966, time 0.0716 | acc 0.7966 | pre 0.8529 | recall 0.8056 | f1 0.8286
Train 19/300, loss 0.0367, time 0.5708
Val 19/300, loss 1.2896, time 0.0730 | acc 0.7458 | pre 0.7692 | recall 0.8333 | f1 0.8000
Train 20/300, loss 0.0172, time 0.6907
Val 20/300, loss 1.2948, time 0.0717 | acc 0.7288 | pre 0.7632 | recall 0.8056 | f1 0.7838
Train 21/300, loss 0.0120, time 0.6302
Val 21/300, loss 1.3318, time 0.0754 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 22/300, loss 0.0193, time 0.6406
Val 22/300, loss 1.3031, time 0.0751 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 23/300, loss 0.0121, time 0.6394
Val 23/300, loss 1.3009, time 0.0757 | acc 0.7627 | pre 0.7895 | recall 0.8333 | f1 0.8108
Train 24/300, loss 0.0076, time 0.6499
Val 24/300, loss 1.2907, time 0.0751 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 25/300, loss 0.0112, time 0.6487
Val 25/300, loss 1.3124, time 0.0756 | acc 0.7627 | pre 0.7750 | recall 0.8611 | f1 0.8158
Train 26/300, loss 0.0037, time 0.6463
Val 26/300, loss 1.2953, time 0.0761 | acc 0.7458 | pre 0.7561 | recall 0.8611 | f1 0.8052
Train 27/300, loss 0.0024, time 0.6344
Val 27/300, loss 1.4529, time 0.0755 | acc 0.7458 | pre 0.7561 | recall 0.8611 | f1 0.8052
Train 28/300, loss 0.0015, time 0.6389
Val 28/300, loss 1.4614, time 0.0760 | acc 0.7458 | pre 0.7561 | recall 0.8611 | f1 0.8052
Train 29/300, loss 0.0013, time 0.6327
Val 29/300, loss 1.4991, time 0.0768 | acc 0.7627 | pre 0.8056 | recall 0.8056 | f1 0.8056
Train 30/300, loss 0.0025, time 0.6586
Val 30/300, loss 1.6070, time 0.0780 | acc 0.7627 | pre 0.7750 | recall 0.8611 | f1 0.8158
Train 31/300, loss 0.0025, time 0.6553
Val 31/300, loss 1.7464, time 0.0775 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 32/300, loss 0.0012, time 0.6398
Val 32/300, loss 1.8133, time 0.0764 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 33/300, loss 0.0011, time 0.6432
Val 33/300, loss 1.9080, time 0.0777 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 34/300, loss 0.0044, time 0.6410
Val 34/300, loss 1.7885, time 0.0754 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 35/300, loss 0.0013, time 0.6391
Val 35/300, loss 1.7300, time 0.0744 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 36/300, loss 0.0029, time 0.6433
Val 36/300, loss 1.6432, time 0.0758 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 37/300, loss 0.0055, time 0.6456
Val 37/300, loss 2.1213, time 0.0758 | acc 0.7797 | pre 0.8485 | recall 0.7778 | f1 0.8116
Train 38/300, loss 0.1683, time 0.6578
Val 38/300, loss 1.4191, time 0.0747 | acc 0.7458 | pre 0.8387 | recall 0.7222 | f1 0.7761
Train 39/300, loss 0.0926, time 0.6481
Val 39/300, loss 1.6493, time 0.0744 | acc 0.6780 | pre 0.6604 | recall 0.9722 | f1 0.7865
Train 40/300, loss 0.1051, time 0.6412
Val 40/300, loss 1.4471, time 0.0745 | acc 0.7627 | pre 0.8438 | recall 0.7500 | f1 0.7941
Train 41/300, loss 0.0429, time 0.6421
Val 41/300, loss 0.9944, time 0.0745 | acc 0.8136 | pre 0.8571 | recall 0.8333 | f1 0.8451
Train 42/300, loss 0.0277, time 0.6501
Val 42/300, loss 0.8045, time 0.0745 | acc 0.8475 | pre 0.8462 | recall 0.9167 | f1 0.8800
Train 43/300, loss 0.0295, time 0.6411
Val 43/300, loss 1.0145, time 0.0743 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 44/300, loss 0.0236, time 0.6365
Val 44/300, loss 1.1423, time 0.0754 | acc 0.7966 | pre 0.8333 | recall 0.8333 | f1 0.8333
Train 45/300, loss 0.0252, time 0.6319
Val 45/300, loss 1.2015, time 0.0759 | acc 0.7797 | pre 0.8485 | recall 0.7778 | f1 0.8116
Train 46/300, loss 0.0086, time 0.6503
Val 46/300, loss 1.5964, time 0.0758 | acc 0.7966 | pre 0.8529 | recall 0.8056 | f1 0.8286
Train 47/300, loss 0.0255, time 0.6384
Val 47/300, loss 1.1922, time 0.0758 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 48/300, loss 0.0172, time 0.6448
Val 48/300, loss 1.1325, time 0.0759 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 49/300, loss 0.0053, time 0.6347
Val 49/300, loss 1.1113, time 0.0759 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 50/300, loss 0.0134, time 0.6423
Val 50/300, loss 1.2079, time 0.0759 | acc 0.7797 | pre 0.8108 | recall 0.8333 | f1 0.8219
Train 51/300, loss 0.0128, time 0.6480
Val 51/300, loss 1.4897, time 0.0750 | acc 0.7797 | pre 0.8108 | recall 0.8333 | f1 0.8219
Train 52/300, loss 0.0162, time 0.6342
Val 52/300, loss 1.5490, time 0.0759 | acc 0.7797 | pre 0.8286 | recall 0.8056 | f1 0.8169
Train 53/300, loss 0.0033, time 0.6433
Val 53/300, loss 1.4697, time 0.0759 | acc 0.7797 | pre 0.8286 | recall 0.8056 | f1 0.8169
Train 54/300, loss 0.0124, time 0.6522
Val 54/300, loss 1.2914, time 0.0760 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 55/300, loss 0.0038, time 0.6576
Val 55/300, loss 1.2036, time 0.0760 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 56/300, loss 0.0031, time 0.6523
Val 56/300, loss 1.2459, time 0.0761 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 57/300, loss 0.0016, time 0.6392
Val 57/300, loss 1.3159, time 0.0758 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 58/300, loss 0.0018, time 0.6611
Val 58/300, loss 1.3800, time 0.0775 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 59/300, loss 0.0011, time 0.6444
Val 59/300, loss 1.4404, time 0.0779 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 60/300, loss 0.0021, time 0.6433
Val 60/300, loss 1.5234, time 0.0778 | acc 0.7966 | pre 0.8333 | recall 0.8333 | f1 0.8333
Train 61/300, loss 0.0007, time 0.6476
Val 61/300, loss 1.4865, time 0.0776 | acc 0.7966 | pre 0.8333 | recall 0.8333 | f1 0.8333
Train 62/300, loss 0.0035, time 0.6421
Val 62/300, loss 1.4341, time 0.0773 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 63/300, loss 0.0025, time 0.6569
Val 63/300, loss 1.3206, time 0.0775 | acc 0.7627 | pre 0.7895 | recall 0.8333 | f1 0.8108
Train 64/300, loss 0.0040, time 0.6395
Val 64/300, loss 1.5195, time 0.0773 | acc 0.7458 | pre 0.7838 | recall 0.8056 | f1 0.7945
Train 65/300, loss 0.0150, time 0.6427
Val 65/300, loss 1.5680, time 0.0774 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 66/300, loss 0.0351, time 0.6423
Val 66/300, loss 1.9564, time 0.0756 | acc 0.7797 | pre 0.7556 | recall 0.9444 | f1 0.8395
Train 67/300, loss 0.0797, time 0.6452
Val 67/300, loss 1.6343, time 0.0758 | acc 0.6949 | pre 0.7250 | recall 0.8056 | f1 0.7632
Train 68/300, loss 0.0940, time 0.6538
Val 68/300, loss 1.5057, time 0.0758 | acc 0.7458 | pre 0.7838 | recall 0.8056 | f1 0.7945
Train 69/300, loss 0.0467, time 0.6456
Val 69/300, loss 1.7420, time 0.0758 | acc 0.7627 | pre 0.7750 | recall 0.8611 | f1 0.8158
Train 70/300, loss 0.0300, time 0.6580
Val 70/300, loss 1.4601, time 0.0767 | acc 0.7458 | pre 0.7838 | recall 0.8056 | f1 0.7945
Train 71/300, loss 0.0170, time 0.6572
Val 71/300, loss 1.5488, time 0.0775 | acc 0.7627 | pre 0.8056 | recall 0.8056 | f1 0.8056
Train 72/300, loss 0.0235, time 0.6472
Val 72/300, loss 1.7090, time 0.0774 | acc 0.7458 | pre 0.7838 | recall 0.8056 | f1 0.7945
Train 73/300, loss 0.0075, time 0.6470
Val 73/300, loss 1.7544, time 0.0774 | acc 0.7458 | pre 0.7692 | recall 0.8333 | f1 0.8000
Train 74/300, loss 0.0123, time 0.6432
Val 74/300, loss 1.6772, time 0.0777 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 75/300, loss 0.0104, time 0.6411
Val 75/300, loss 1.6000, time 0.0772 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 76/300, loss 0.0013, time 0.6417
Val 76/300, loss 1.5491, time 0.0787 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 77/300, loss 0.0035, time 0.6401
Val 77/300, loss 1.6275, time 0.0774 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 78/300, loss 0.0023, time 0.6627
Val 78/300, loss 1.6814, time 0.0777 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 79/300, loss 0.0024, time 0.6656
Val 79/300, loss 1.7900, time 0.0756 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 80/300, loss 0.0010, time 0.6365
Val 80/300, loss 1.7935, time 0.0781 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 81/300, loss 0.0023, time 0.6881
Val 81/300, loss 1.7811, time 0.0741 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 82/300, loss 0.0012, time 0.6527
Val 82/300, loss 1.8046, time 0.0779 | acc 0.7458 | pre 0.7838 | recall 0.8056 | f1 0.7945
Train 83/300, loss 0.0040, time 0.7179
Val 83/300, loss 1.7777, time 0.0741 | acc 0.7797 | pre 0.8286 | recall 0.8056 | f1 0.8169
Train 84/300, loss 0.0014, time 0.6286
Val 84/300, loss 1.9618, time 0.0769 | acc 0.7966 | pre 0.8333 | recall 0.8333 | f1 0.8333
Train 85/300, loss 0.0170, time 0.6080
Val 85/300, loss 2.0157, time 0.0745 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 86/300, loss 0.0370, time 0.6400
Val 86/300, loss 2.1267, time 0.0775 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 87/300, loss 0.0462, time 0.6835
Val 87/300, loss 2.0155, time 0.0744 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 88/300, loss 0.0093, time 0.6326
Val 88/300, loss 1.9794, time 0.0770 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 89/300, loss 0.0014, time 0.6259
Val 89/300, loss 1.9372, time 0.0757 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 90/300, loss 0.0009, time 0.6264
Val 90/300, loss 1.9447, time 0.0765 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 91/300, loss 0.0099, time 0.6353
Val 91/300, loss 2.0475, time 0.0761 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 92/300, loss 0.0010, time 0.6403
Val 92/300, loss 2.1567, time 0.0786 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 93/300, loss 0.0005, time 0.7165
Val 93/300, loss 2.1824, time 0.0748 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 94/300, loss 0.0017, time 0.6527
Val 94/300, loss 2.2219, time 0.0788 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 95/300, loss 0.0032, time 0.6356
Val 95/300, loss 2.2066, time 0.0765 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 96/300, loss 0.0019, time 0.6549
Val 96/300, loss 2.1974, time 0.0785 | acc 0.7458 | pre 0.7561 | recall 0.8611 | f1 0.8052
Train 97/300, loss 0.0015, time 0.6983
Val 97/300, loss 2.1339, time 0.0753 | acc 0.7458 | pre 0.7561 | recall 0.8611 | f1 0.8052
Train 98/300, loss 0.0030, time 0.6349
Val 98/300, loss 2.1417, time 0.0780 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 99/300, loss 0.0008, time 0.6415
Val 99/300, loss 2.2361, time 0.0766 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 100/300, loss 0.0009, time 0.6438
Val 100/300, loss 2.2994, time 0.0776 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 101/300, loss 0.0022, time 0.6910
Val 101/300, loss 2.4236, time 0.0736 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 102/300, loss 0.0013, time 0.6321
Val 102/300, loss 2.5753, time 0.0751 | acc 0.7627 | pre 0.7750 | recall 0.8611 | f1 0.8158
Train 103/300, loss 0.0059, time 0.6910
Val 103/300, loss 2.4475, time 0.0751 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 104/300, loss 0.0039, time 0.6453
Val 104/300, loss 2.2939, time 0.0772 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 105/300, loss 0.0055, time 0.6500
Val 105/300, loss 2.1996, time 0.0775 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 106/300, loss 0.0155, time 0.6459
Val 106/300, loss 1.9944, time 0.0781 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 107/300, loss 0.0030, time 0.6504
Val 107/300, loss 2.1418, time 0.0789 | acc 0.7458 | pre 0.7561 | recall 0.8611 | f1 0.8052
Train 108/300, loss 0.0188, time 0.6542
Val 108/300, loss 2.0599, time 0.0781 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 109/300, loss 0.0096, time 0.6656
Val 109/300, loss 1.9992, time 0.0780 | acc 0.7627 | pre 0.7895 | recall 0.8333 | f1 0.8108
Train 110/300, loss 0.0557, time 0.6604
Val 110/300, loss 1.9088, time 0.0774 | acc 0.7797 | pre 0.8108 | recall 0.8333 | f1 0.8219
Train 111/300, loss 0.0243, time 0.6553
Val 111/300, loss 1.7404, time 0.0778 | acc 0.7627 | pre 0.8056 | recall 0.8056 | f1 0.8056
Train 112/300, loss 0.0174, time 0.6428
Val 112/300, loss 1.6421, time 0.0777 | acc 0.7627 | pre 0.7750 | recall 0.8611 | f1 0.8158
Train 113/300, loss 0.0064, time 0.6497
Val 113/300, loss 1.6911, time 0.0779 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 114/300, loss 0.0106, time 0.6453
Val 114/300, loss 1.7695, time 0.0779 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 115/300, loss 0.0018, time 0.6593
Val 115/300, loss 1.7588, time 0.0772 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 116/300, loss 0.0100, time 0.6502
Val 116/300, loss 1.8156, time 0.0781 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 117/300, loss 0.0015, time 0.6561
Val 117/300, loss 1.9207, time 0.0779 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 118/300, loss 0.0019, time 0.6644
Val 118/300, loss 1.9039, time 0.0780 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 119/300, loss 0.0029, time 0.6420
Val 119/300, loss 1.9650, time 0.0779 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 120/300, loss 0.0013, time 0.6506
Val 120/300, loss 1.9513, time 0.0748 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 121/300, loss 0.0011, time 0.6429
Val 121/300, loss 1.9813, time 0.0763 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 122/300, loss 0.0011, time 0.6411
Val 122/300, loss 2.0556, time 0.0761 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 123/300, loss 0.0006, time 0.6427
Val 123/300, loss 2.0599, time 0.0764 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 124/300, loss 0.0071, time 0.6470
Val 124/300, loss 2.3260, time 0.0762 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 125/300, loss 0.0024, time 0.6325
Val 125/300, loss 2.4427, time 0.0762 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 126/300, loss 0.0006, time 0.6579
Val 126/300, loss 2.5921, time 0.0766 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 127/300, loss 0.0036, time 0.6442
Val 127/300, loss 2.5935, time 0.0761 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 128/300, loss 0.0008, time 0.6363
Val 128/300, loss 2.5125, time 0.0763 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 129/300, loss 0.0005, time 0.6425
Val 129/300, loss 2.5331, time 0.0762 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 130/300, loss 0.0005, time 0.6510
Val 130/300, loss 2.5310, time 0.0778 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 131/300, loss 0.0004, time 0.6460
Val 131/300, loss 2.4731, time 0.0780 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 132/300, loss 0.0002, time 0.6549
Val 132/300, loss 2.5021, time 0.0780 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 133/300, loss 0.0002, time 0.6478
Val 133/300, loss 2.5000, time 0.0782 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 134/300, loss 0.0003, time 0.6489
Val 134/300, loss 2.5370, time 0.0779 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 135/300, loss 0.0002, time 0.6525
Val 135/300, loss 2.5421, time 0.0778 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 136/300, loss 0.0003, time 0.6514
Val 136/300, loss 2.5552, time 0.0779 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 137/300, loss 0.0002, time 0.6396
Val 137/300, loss 2.4860, time 0.0777 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 138/300, loss 0.0001, time 0.6690
Val 138/300, loss 2.4553, time 0.0780 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 139/300, loss 0.0004, time 0.6441
Val 139/300, loss 2.4439, time 0.0780 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 140/300, loss 0.0001, time 0.6480
Val 140/300, loss 2.5114, time 0.0780 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 141/300, loss 0.0000, time 0.6431
Val 141/300, loss 2.4970, time 0.0779 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 142/300, loss 0.0003, time 0.6504
Val 142/300, loss 2.5586, time 0.0780 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 143/300, loss 0.0001, time 0.6457
Val 143/300, loss 2.5503, time 0.0780 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 144/300, loss 0.0005, time 0.6525
Val 144/300, loss 2.5766, time 0.0779 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 145/300, loss 0.0002, time 0.6523
Val 145/300, loss 2.3210, time 0.0778 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 146/300, loss 0.0010, time 0.6641
Val 146/300, loss 2.2188, time 0.0777 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 147/300, loss 0.0010, time 0.6332
Val 147/300, loss 2.3220, time 0.0780 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 148/300, loss 0.0001, time 0.6477
Val 148/300, loss 2.5229, time 0.0778 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 149/300, loss 0.0057, time 0.6640
Val 149/300, loss 2.5896, time 0.0763 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 150/300, loss 0.0031, time 0.6363
Val 150/300, loss 2.4735, time 0.0747 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 151/300, loss 0.0014, time 0.6435
Val 151/300, loss 2.1917, time 0.0751 | acc 0.7797 | pre 0.8108 | recall 0.8333 | f1 0.8219
Train 152/300, loss 0.0099, time 0.6378
Val 152/300, loss 2.1567, time 0.0748 | acc 0.7797 | pre 0.8108 | recall 0.8333 | f1 0.8219
Train 153/300, loss 0.0117, time 0.6357
Val 153/300, loss 2.0437, time 0.0747 | acc 0.7966 | pre 0.8333 | recall 0.8333 | f1 0.8333
Train 154/300, loss 0.0077, time 0.6482
Val 154/300, loss 2.0017, time 0.0744 | acc 0.7966 | pre 0.8333 | recall 0.8333 | f1 0.8333
Train 155/300, loss 0.0038, time 0.6340
Val 155/300, loss 2.1130, time 0.0743 | acc 0.7797 | pre 0.8108 | recall 0.8333 | f1 0.8219
Train 156/300, loss 0.0046, time 0.6386
Val 156/300, loss 2.2102, time 0.0759 | acc 0.7966 | pre 0.8333 | recall 0.8333 | f1 0.8333
Train 157/300, loss 0.0004, time 0.6389
Val 157/300, loss 2.3669, time 0.0745 | acc 0.7966 | pre 0.8333 | recall 0.8333 | f1 0.8333
Train 158/300, loss 0.0004, time 0.6506
Val 158/300, loss 2.3926, time 0.0762 | acc 0.7966 | pre 0.8333 | recall 0.8333 | f1 0.8333
Train 159/300, loss 0.0010, time 0.6423
Val 159/300, loss 2.4224, time 0.0759 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 160/300, loss 0.0015, time 0.6281
Val 160/300, loss 2.4795, time 0.0760 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 161/300, loss 0.0001, time 0.6823
Val 161/300, loss 2.4846, time 0.0729 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 162/300, loss 0.0002, time 0.6062
Val 162/300, loss 2.5248, time 0.0757 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 163/300, loss 0.0004, time 0.6859
Val 163/300, loss 2.5678, time 0.1009 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 164/300, loss 0.0002, time 0.6355
Val 164/300, loss 2.5279, time 0.0775 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 165/300, loss 0.0026, time 0.6684
Val 165/300, loss 2.5367, time 0.0795 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 166/300, loss 0.0002, time 0.6437
Val 166/300, loss 2.8927, time 0.0776 | acc 0.7797 | pre 0.8286 | recall 0.8056 | f1 0.8169
Train 167/300, loss 0.0029, time 0.6189
Val 167/300, loss 2.9168, time 0.1028 | acc 0.7797 | pre 0.8286 | recall 0.8056 | f1 0.8169
Train 168/300, loss 0.0130, time 0.6139
Val 168/300, loss 3.2426, time 0.0771 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 169/300, loss 0.0469, time 0.6313
Val 169/300, loss 2.6776, time 0.0839 | acc 0.7627 | pre 0.7750 | recall 0.8611 | f1 0.8158
Train 170/300, loss 0.0030, time 0.6846
Val 170/300, loss 2.2326, time 0.0769 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 171/300, loss 0.0129, time 0.6427
Val 171/300, loss 2.0206, time 0.0834 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 172/300, loss 0.0284, time 0.6816
Val 172/300, loss 1.7253, time 0.0762 | acc 0.7627 | pre 0.7895 | recall 0.8333 | f1 0.8108
Train 173/300, loss 0.0421, time 0.6252
Val 173/300, loss 1.7447, time 0.0772 | acc 0.7966 | pre 0.7727 | recall 0.9444 | f1 0.8500
Train 174/300, loss 0.0308, time 0.6566
Val 174/300, loss 1.9579, time 0.0760 | acc 0.7966 | pre 0.7857 | recall 0.9167 | f1 0.8462
Train 175/300, loss 0.0272, time 0.6280
Val 175/300, loss 1.5974, time 0.0747 | acc 0.7797 | pre 0.8108 | recall 0.8333 | f1 0.8219
Train 176/300, loss 0.0084, time 0.6230
Val 176/300, loss 1.9765, time 0.0771 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 177/300, loss 0.0108, time 0.6453
Val 177/300, loss 1.9899, time 0.0793 | acc 0.6102 | pre 0.9333 | recall 0.3889 | f1 0.5490
Train 178/300, loss 0.0343, time 0.6823
Val 178/300, loss 1.7389, time 0.0752 | acc 0.7119 | pre 0.9130 | recall 0.5833 | f1 0.7119
Train 179/300, loss 0.0331, time 0.6608
Val 179/300, loss 1.7204, time 0.0778 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 180/300, loss 0.0831, time 0.6866
Val 180/300, loss 1.5937, time 0.0747 | acc 0.7966 | pre 0.8529 | recall 0.8056 | f1 0.8286
Train 181/300, loss 0.3705, time 0.6413
Val 181/300, loss 1.5129, time 0.0781 | acc 0.7966 | pre 0.8333 | recall 0.8333 | f1 0.8333
Train 182/300, loss 0.0339, time 0.6847
Val 182/300, loss 1.1664, time 0.0755 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 183/300, loss 0.0349, time 0.6286
Val 183/300, loss 1.4378, time 0.0775 | acc 0.7458 | pre 0.7561 | recall 0.8611 | f1 0.8052
Train 184/300, loss 0.0292, time 0.6706
Val 184/300, loss 1.6779, time 0.0759 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 185/300, loss 0.0121, time 0.6412
Val 185/300, loss 1.5698, time 0.0777 | acc 0.7627 | pre 0.7750 | recall 0.8611 | f1 0.8158
Train 186/300, loss 0.0077, time 0.6451
Val 186/300, loss 1.4087, time 0.0719 | acc 0.7627 | pre 0.7750 | recall 0.8611 | f1 0.8158
Train 187/300, loss 0.0183, time 0.5326
Val 187/300, loss 1.4956, time 0.0731 | acc 0.7797 | pre 0.7674 | recall 0.9167 | f1 0.8354
Train 188/300, loss 0.0063, time 0.5898
Val 188/300, loss 1.6020, time 0.0764 | acc 0.7797 | pre 0.7674 | recall 0.9167 | f1 0.8354
Train 189/300, loss 0.0196, time 0.6371
Val 189/300, loss 1.5089, time 0.0761 | acc 0.7627 | pre 0.7750 | recall 0.8611 | f1 0.8158
Train 190/300, loss 0.0061, time 0.6452
Val 190/300, loss 1.5063, time 0.0767 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 191/300, loss 0.0037, time 0.6325
Val 191/300, loss 1.5334, time 0.0751 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 192/300, loss 0.0035, time 0.6320
Val 192/300, loss 1.5414, time 0.0766 | acc 0.7627 | pre 0.7750 | recall 0.8611 | f1 0.8158
Train 193/300, loss 0.0051, time 0.6449
Val 193/300, loss 1.6518, time 0.0767 | acc 0.7627 | pre 0.7750 | recall 0.8611 | f1 0.8158
Train 194/300, loss 0.0024, time 0.6480
Val 194/300, loss 1.7051, time 0.0762 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 195/300, loss 0.0022, time 0.6341
Val 195/300, loss 1.8208, time 0.0767 | acc 0.7627 | pre 0.7750 | recall 0.8611 | f1 0.8158
Train 196/300, loss 0.0015, time 0.6379
Val 196/300, loss 1.8059, time 0.0767 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 197/300, loss 0.0269, time 0.6721
Val 197/300, loss 1.6546, time 0.0775 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 198/300, loss 0.0218, time 0.6423
Val 198/300, loss 1.7511, time 0.0773 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 199/300, loss 0.0358, time 0.6350
Val 199/300, loss 1.8716, time 0.0774 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 200/300, loss 0.0091, time 0.6605
Val 200/300, loss 1.9169, time 0.0772 | acc 0.7966 | pre 0.8333 | recall 0.8333 | f1 0.8333
Train 201/300, loss 0.0040, time 0.6508
Val 201/300, loss 2.0152, time 0.0773 | acc 0.7797 | pre 0.8108 | recall 0.8333 | f1 0.8219
Train 202/300, loss 0.0094, time 0.6364
Val 202/300, loss 1.9985, time 0.0772 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 203/300, loss 0.0057, time 0.6457
Val 203/300, loss 2.0194, time 0.0774 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 204/300, loss 0.0049, time 0.6516
Val 204/300, loss 2.0392, time 0.0774 | acc 0.7627 | pre 0.7750 | recall 0.8611 | f1 0.8158
Train 205/300, loss 0.0103, time 0.6454
Val 205/300, loss 2.0756, time 0.0769 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 206/300, loss 0.0021, time 0.6454
Val 206/300, loss 2.0789, time 0.0772 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 207/300, loss 0.0218, time 0.6522
Val 207/300, loss 2.0766, time 0.0772 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 208/300, loss 0.0025, time 0.6448
Val 208/300, loss 1.9981, time 0.0775 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 209/300, loss 0.0092, time 0.6559
Val 209/300, loss 1.8531, time 0.0774 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 210/300, loss 0.0226, time 0.6520
Val 210/300, loss 1.5915, time 0.0775 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 211/300, loss 0.0063, time 0.6398
Val 211/300, loss 1.6787, time 0.0776 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 212/300, loss 0.0141, time 0.6597
Val 212/300, loss 1.7113, time 0.0776 | acc 0.7627 | pre 0.7750 | recall 0.8611 | f1 0.8158
Train 213/300, loss 0.0106, time 0.6403
Val 213/300, loss 1.7065, time 0.0773 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 214/300, loss 0.0238, time 0.6419
Val 214/300, loss 1.7976, time 0.0775 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 215/300, loss 0.0234, time 0.6619
Val 215/300, loss 1.8499, time 0.0774 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 216/300, loss 0.0191, time 0.6440
Val 216/300, loss 1.7104, time 0.0772 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 217/300, loss 0.0088, time 0.6610
Val 217/300, loss 1.6794, time 0.0772 | acc 0.7627 | pre 0.7750 | recall 0.8611 | f1 0.8158
Train 218/300, loss 0.0115, time 0.6599
Val 218/300, loss 1.7498, time 0.0775 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 219/300, loss 0.0104, time 0.6449
Val 219/300, loss 1.9330, time 0.0776 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 220/300, loss 0.0029, time 0.6447
Val 220/300, loss 1.9247, time 0.0776 | acc 0.7966 | pre 0.8333 | recall 0.8333 | f1 0.8333
Train 221/300, loss 0.0129, time 0.6549
Val 221/300, loss 1.9837, time 0.0775 | acc 0.7966 | pre 0.8333 | recall 0.8333 | f1 0.8333
Train 222/300, loss 0.0068, time 0.6378
Val 222/300, loss 1.7790, time 0.0773 | acc 0.7966 | pre 0.8333 | recall 0.8333 | f1 0.8333
Train 223/300, loss 0.0118, time 0.6449
Val 223/300, loss 1.6426, time 0.0773 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 224/300, loss 0.0055, time 0.6437
Val 224/300, loss 1.5992, time 0.0773 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 225/300, loss 0.0067, time 0.6420
Val 225/300, loss 1.6000, time 0.0772 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 226/300, loss 0.0043, time 0.6557
Val 226/300, loss 1.6897, time 0.0768 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 227/300, loss 0.0041, time 0.6440
Val 227/300, loss 1.5911, time 0.0774 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 228/300, loss 0.0014, time 0.6512
Val 228/300, loss 1.5869, time 0.0772 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 229/300, loss 0.0128, time 0.6387
Val 229/300, loss 1.7692, time 0.0774 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 230/300, loss 0.0078, time 0.6451
Val 230/300, loss 1.9243, time 0.0773 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 231/300, loss 0.0044, time 0.6444
Val 231/300, loss 1.9445, time 0.0780 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 232/300, loss 0.0026, time 0.6434
Val 232/300, loss 1.9187, time 0.0768 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 233/300, loss 0.0015, time 0.6561
Val 233/300, loss 1.9200, time 0.0767 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 234/300, loss 0.0003, time 0.6457
Val 234/300, loss 1.9540, time 0.0774 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 235/300, loss 0.0006, time 0.6485
Val 235/300, loss 1.9916, time 0.0775 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 236/300, loss 0.0024, time 0.6455
Val 236/300, loss 1.8941, time 0.0774 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 237/300, loss 0.0017, time 0.6418
Val 237/300, loss 1.8490, time 0.0775 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 238/300, loss 0.0008, time 0.6494
Val 238/300, loss 1.8655, time 0.0775 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 239/300, loss 0.0010, time 0.6592
Val 239/300, loss 1.9032, time 0.0777 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 240/300, loss 0.0001, time 0.6551
Val 240/300, loss 1.9347, time 0.0778 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 241/300, loss 0.0005, time 0.6452
Val 241/300, loss 1.9808, time 0.0774 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 242/300, loss 0.0013, time 0.6550
Val 242/300, loss 2.0336, time 0.0767 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 243/300, loss 0.0002, time 0.6563
Val 243/300, loss 2.0030, time 0.0773 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 244/300, loss 0.0029, time 0.6615
Val 244/300, loss 2.0271, time 0.0753 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 245/300, loss 0.0002, time 0.6305
Val 245/300, loss 2.1675, time 0.0767 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 246/300, loss 0.0004, time 0.7103
Val 246/300, loss 2.2186, time 0.0730 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 247/300, loss 0.0002, time 0.6418
Val 247/300, loss 2.2375, time 0.0776 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 248/300, loss 0.0008, time 0.6686
Val 248/300, loss 2.2243, time 0.0745 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 249/300, loss 0.0003, time 0.6370
Val 249/300, loss 2.3174, time 0.0761 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 250/300, loss 0.0063, time 0.6304
Val 250/300, loss 2.3322, time 0.0737 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 251/300, loss 0.1124, time 0.6139
Val 251/300, loss 1.9104, time 0.0759 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 252/300, loss 0.0883, time 0.6526
Val 252/300, loss 1.6476, time 0.0745 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 253/300, loss 0.0068, time 0.6400
Val 253/300, loss 1.6463, time 0.0754 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 254/300, loss 0.0189, time 0.6426
Val 254/300, loss 1.7150, time 0.0745 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 255/300, loss 0.0130, time 0.5969
Val 255/300, loss 1.6644, time 0.0769 | acc 0.7966 | pre 0.7857 | recall 0.9167 | f1 0.8462
Train 256/300, loss 0.0023, time 0.7192
Val 256/300, loss 1.4711, time 0.0743 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 257/300, loss 0.0014, time 0.6409
Val 257/300, loss 1.3531, time 0.0764 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 258/300, loss 0.0007, time 0.6590
Val 258/300, loss 1.3322, time 0.0743 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 259/300, loss 0.0006, time 0.6272
Val 259/300, loss 1.3643, time 0.0753 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 260/300, loss 0.0045, time 0.7086
Val 260/300, loss 1.2540, time 0.0745 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 261/300, loss 0.0012, time 0.6185
Val 261/300, loss 1.2174, time 0.0773 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 262/300, loss 0.0009, time 0.7066
Val 262/300, loss 1.2630, time 0.0721 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 263/300, loss 0.0008, time 0.6173
Val 263/300, loss 1.3045, time 0.0755 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 264/300, loss 0.0006, time 0.6443
Val 264/300, loss 1.3259, time 0.0726 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 265/300, loss 0.0008, time 0.6194
Val 265/300, loss 1.3380, time 0.0756 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 266/300, loss 0.0004, time 0.6399
Val 266/300, loss 1.4241, time 0.0749 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 267/300, loss 0.0006, time 0.6211
Val 267/300, loss 1.4190, time 0.0762 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 268/300, loss 0.0001, time 0.6375
Val 268/300, loss 1.4560, time 0.1480 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 269/300, loss 0.0002, time 0.6159
Val 269/300, loss 1.4624, time 0.0762 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 270/300, loss 0.0004, time 0.6523
Val 270/300, loss 1.4947, time 0.0761 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 271/300, loss 0.0171, time 0.6508
Val 271/300, loss 1.5564, time 0.0771 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 272/300, loss 0.0063, time 0.6454
Val 272/300, loss 1.8553, time 0.0767 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 273/300, loss 0.0409, time 0.6539
Val 273/300, loss 1.5928, time 0.0762 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 274/300, loss 0.0134, time 0.6357
Val 274/300, loss 2.5596, time 0.0769 | acc 0.7627 | pre 0.7391 | recall 0.9444 | f1 0.8293
Train 275/300, loss 0.0367, time 0.6509
Val 275/300, loss 2.1254, time 0.0769 | acc 0.7458 | pre 0.7333 | recall 0.9167 | f1 0.8148
Train 276/300, loss 0.0066, time 0.6541
Val 276/300, loss 1.9905, time 0.0769 | acc 0.7458 | pre 0.7333 | recall 0.9167 | f1 0.8148
Train 277/300, loss 0.0344, time 0.6428
Val 277/300, loss 1.7174, time 0.0769 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 278/300, loss 0.0161, time 0.6437
Val 278/300, loss 1.6579, time 0.0768 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 279/300, loss 0.0007, time 0.6424
Val 279/300, loss 1.6317, time 0.0774 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 280/300, loss 0.0099, time 0.6455
Val 280/300, loss 1.6128, time 0.0766 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 281/300, loss 0.0006, time 0.6358
Val 281/300, loss 1.5649, time 0.0770 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 282/300, loss 0.0030, time 0.6382
Val 282/300, loss 1.5935, time 0.0753 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 283/300, loss 0.0043, time 0.6368
Val 283/300, loss 1.6273, time 0.0753 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 284/300, loss 0.0018, time 0.6336
Val 284/300, loss 1.7804, time 0.0766 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 285/300, loss 0.0007, time 0.6432
Val 285/300, loss 1.8546, time 0.0766 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 286/300, loss 0.0005, time 0.6446
Val 286/300, loss 1.9178, time 0.0768 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 287/300, loss 0.0030, time 0.6397
Val 287/300, loss 1.8828, time 0.0767 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 288/300, loss 0.0007, time 0.6383
Val 288/300, loss 1.8870, time 0.0767 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 289/300, loss 0.0001, time 0.6401
Val 289/300, loss 1.8753, time 0.0769 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 290/300, loss 0.0001, time 0.6479
Val 290/300, loss 1.9078, time 0.0766 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 291/300, loss 0.0028, time 0.6446
Val 291/300, loss 1.9031, time 0.0767 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 292/300, loss 0.0008, time 0.6440
Val 292/300, loss 2.1695, time 0.0766 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 293/300, loss 0.0019, time 0.6416
Val 293/300, loss 2.2171, time 0.0764 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 294/300, loss 0.0002, time 0.6355
Val 294/300, loss 2.2520, time 0.0767 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 295/300, loss 0.0003, time 0.6413
Val 295/300, loss 2.2300, time 0.0770 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 296/300, loss 0.0001, time 0.6440
Val 296/300, loss 2.2628, time 0.0769 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 297/300, loss 0.0001, time 0.6407
Val 297/300, loss 2.2689, time 0.0771 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 298/300, loss 0.0018, time 0.6848
Val 298/300, loss 2.2425, time 0.0762 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 299/300, loss 0.0001, time 0.6430
Val 299/300, loss 2.2761, time 0.0752 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 300/300, loss 0.0001, time 0.6500
Val 300/300, loss 2.2880, time 0.0752 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
best epoch: 41 acc: 0.8475 | Precision: 0.8462 | recall 0.9167 | f1 0.8800
Total time: 217.3120
Fold 4 / 5
GraphTransformer(
(embedding): Linear(in_features=4096, out_features=256, bias=False)
(encoder): GraphTransformerEncoder(
(layers): ModuleList(
(0-2): 3 x TransformerEncoderLayer(
(self_attn): Attention()
(linear1): Linear(in_features=256, out_features=128, bias=True)
(dropout): Dropout(p=0.1, inplace=False)
(linear2): Linear(in_features=128, out_features=256, bias=True)
(norm1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(norm2): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(dropout1): Dropout(p=0.1, inplace=False)
(dropout2): Dropout(p=0.1, inplace=False)
)
)
)
(classifier): Sequential(
(0): Linear(in_features=256, out_features=256, bias=True)
(1): ReLU(inplace=True)
(2): Linear(in_features=256, out_features=2, bias=True)
)
)
Total number of parameters: 3096706
Extracting 2-hop subgraphs...
Done!
Extracting 2-hop subgraphs...
Done!
Training...
Train 1/300, loss 0.4730, time 0.6347
Val 1/300, loss 0.6883, time 0.0764 | acc 0.4915 | pre 1.0000 | recall 0.1667 | f1 0.2857
Train 2/300, loss 0.2392, time 0.6346
Val 2/300, loss 0.6882, time 0.0752 | acc 0.4915 | pre 1.0000 | recall 0.1667 | f1 0.2857
Train 3/300, loss 0.1985, time 0.6365
Val 3/300, loss 0.6733, time 0.0753 | acc 0.5593 | pre 1.0000 | recall 0.2778 | f1 0.4348
Train 4/300, loss 0.1661, time 0.6532
Val 4/300, loss 0.6262, time 0.0752 | acc 0.7119 | pre 0.9524 | recall 0.5556 | f1 0.7018
Train 5/300, loss 0.1494, time 0.6346
Val 5/300, loss 0.5679, time 0.0751 | acc 0.7797 | pre 0.9600 | recall 0.6667 | f1 0.7869
Train 6/300, loss 0.1366, time 0.6324
Val 6/300, loss 0.5033, time 0.0752 | acc 0.7966 | pre 0.8529 | recall 0.8056 | f1 0.8286
Train 7/300, loss 0.0945, time 0.6314
Val 7/300, loss 0.4253, time 0.0751 | acc 0.8475 | pre 0.8649 | recall 0.8889 | f1 0.8767
Train 8/300, loss 0.0776, time 0.6312
Val 8/300, loss 0.4568, time 0.0752 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 9/300, loss 0.0724, time 0.6375
Val 9/300, loss 1.5526, time 0.0746 | acc 0.5593 | pre 0.9167 | recall 0.3056 | f1 0.4583
Train 10/300, loss 0.0889, time 0.6451
Val 10/300, loss 0.8628, time 0.0748 | acc 0.7458 | pre 0.8000 | recall 0.7778 | f1 0.7887
Train 11/300, loss 0.0863, time 0.6299
Val 11/300, loss 0.9605, time 0.0749 | acc 0.7797 | pre 0.8710 | recall 0.7500 | f1 0.8060
Train 12/300, loss 0.0510, time 0.6428
Val 12/300, loss 0.8969, time 0.0742 | acc 0.7966 | pre 0.8333 | recall 0.8333 | f1 0.8333
Train 13/300, loss 0.0513, time 0.6321
Val 13/300, loss 0.7720, time 0.0771 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 14/300, loss 0.0632, time 0.6294
Val 14/300, loss 0.9281, time 0.0751 | acc 0.7627 | pre 0.7500 | recall 0.9167 | f1 0.8250
Train 15/300, loss 0.0556, time 0.6476
Val 15/300, loss 1.0010, time 0.0746 | acc 0.7627 | pre 0.7500 | recall 0.9167 | f1 0.8250
Train 16/300, loss 0.0313, time 0.6323
Val 16/300, loss 0.7355, time 0.0749 | acc 0.8305 | pre 0.8421 | recall 0.8889 | f1 0.8649
Train 17/300, loss 0.0299, time 0.6278
Val 17/300, loss 0.8762, time 0.0790 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 18/300, loss 0.0256, time 0.6699
Val 18/300, loss 0.9197, time 0.0789 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 19/300, loss 0.0193, time 0.6388
Val 19/300, loss 1.0568, time 0.0734 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 20/300, loss 0.0100, time 0.6330
Val 20/300, loss 1.1511, time 0.0739 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 21/300, loss 0.0091, time 0.6540
Val 21/300, loss 1.2052, time 0.0751 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 22/300, loss 0.0150, time 0.6243
Val 22/300, loss 1.1856, time 0.0749 | acc 0.8136 | pre 0.8571 | recall 0.8333 | f1 0.8451
Train 23/300, loss 0.0137, time 0.6305
Val 23/300, loss 1.1725, time 0.0756 | acc 0.8136 | pre 0.8571 | recall 0.8333 | f1 0.8451
Train 24/300, loss 0.0119, time 0.6473
Val 24/300, loss 1.1822, time 0.0727 | acc 0.8305 | pre 0.8611 | recall 0.8611 | f1 0.8611
Train 25/300, loss 0.0222, time 0.6257
Val 25/300, loss 1.1732, time 0.0745 | acc 0.8305 | pre 0.8421 | recall 0.8889 | f1 0.8649
Train 26/300, loss 0.0207, time 0.7084
Val 26/300, loss 1.4013, time 0.0727 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 27/300, loss 0.0322, time 0.6356
Val 27/300, loss 1.5190, time 0.0763 | acc 0.6949 | pre 0.6957 | recall 0.8889 | f1 0.7805
Train 28/300, loss 0.0558, time 0.6904
Val 28/300, loss 1.4895, time 0.0736 | acc 0.7119 | pre 0.6939 | recall 0.9444 | f1 0.8000
Train 29/300, loss 0.0371, time 0.6274
Val 29/300, loss 0.9386, time 0.0774 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 30/300, loss 0.0284, time 0.7479
Val 30/300, loss 0.9530, time 0.0734 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 31/300, loss 0.0159, time 0.6174
Val 31/300, loss 1.0392, time 0.0762 | acc 0.8136 | pre 0.8571 | recall 0.8333 | f1 0.8451
Train 32/300, loss 0.0361, time 0.6749
Val 32/300, loss 1.2627, time 0.0732 | acc 0.7966 | pre 0.8529 | recall 0.8056 | f1 0.8286
Train 33/300, loss 0.0669, time 0.5994
Val 33/300, loss 1.0270, time 0.0766 | acc 0.7966 | pre 0.8333 | recall 0.8333 | f1 0.8333
Train 34/300, loss 0.0959, time 0.6602
Val 34/300, loss 1.0067, time 0.0720 | acc 0.7797 | pre 0.8286 | recall 0.8056 | f1 0.8169
Train 35/300, loss 0.0433, time 0.6064
Val 35/300, loss 1.3652, time 0.0750 | acc 0.7797 | pre 0.8710 | recall 0.7500 | f1 0.8060
Train 36/300, loss 0.0630, time 0.6714
Val 36/300, loss 1.2325, time 0.0736 | acc 0.7797 | pre 0.8108 | recall 0.8333 | f1 0.8219
Train 37/300, loss 0.0283, time 0.6128
Val 37/300, loss 1.2298, time 0.0770 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 38/300, loss 0.0481, time 0.6763
Val 38/300, loss 1.6130, time 0.0754 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 39/300, loss 0.0553, time 0.6185
Val 39/300, loss 1.5124, time 0.0765 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 40/300, loss 0.0342, time 0.6052
Val 40/300, loss 1.4769, time 0.1766 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 41/300, loss 0.0425, time 0.5999
Val 41/300, loss 1.2006, time 0.0753 | acc 0.7627 | pre 0.7500 | recall 0.9167 | f1 0.8250
Train 42/300, loss 0.1464, time 0.6093
Val 42/300, loss 1.1979, time 0.1718 | acc 0.7627 | pre 0.7500 | recall 0.9167 | f1 0.8250
Train 43/300, loss 0.0540, time 0.6296
Val 43/300, loss 1.2456, time 0.0760 | acc 0.7458 | pre 0.7838 | recall 0.8056 | f1 0.7945
Train 44/300, loss 0.0551, time 0.6324
Val 44/300, loss 1.0212, time 0.0958 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 45/300, loss 0.0393, time 0.6127
Val 45/300, loss 0.9060, time 0.0751 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 46/300, loss 0.0272, time 0.6362
Val 46/300, loss 0.9009, time 0.0812 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 47/300, loss 0.0184, time 0.6747
Val 47/300, loss 0.9312, time 0.0755 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 48/300, loss 0.0154, time 0.6333
Val 48/300, loss 1.1026, time 0.0758 | acc 0.8644 | pre 0.8889 | recall 0.8889 | f1 0.8889
Train 49/300, loss 0.0095, time 0.6609
Val 49/300, loss 1.2111, time 0.0753 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 50/300, loss 0.0147, time 0.6281
Val 50/300, loss 1.3236, time 0.0760 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 51/300, loss 0.0121, time 0.6387
Val 51/300, loss 1.2395, time 0.0769 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 52/300, loss 0.0143, time 0.6452
Val 52/300, loss 0.8609, time 0.0763 | acc 0.8305 | pre 0.8421 | recall 0.8889 | f1 0.8649
Train 53/300, loss 0.0131, time 0.6412
Val 53/300, loss 0.9076, time 0.0766 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 54/300, loss 0.0063, time 0.6510
Val 54/300, loss 0.9734, time 0.0769 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 55/300, loss 0.0024, time 0.6573
Val 55/300, loss 1.0900, time 0.0769 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 56/300, loss 0.0025, time 0.6511
Val 56/300, loss 1.2103, time 0.0769 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 57/300, loss 0.0024, time 0.6400
Val 57/300, loss 1.3296, time 0.0772 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 58/300, loss 0.0010, time 0.6319
Val 58/300, loss 1.4193, time 0.0752 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 59/300, loss 0.0032, time 0.6380
Val 59/300, loss 1.3482, time 0.0836 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 60/300, loss 0.0013, time 0.6508
Val 60/300, loss 1.3513, time 0.0752 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 61/300, loss 0.0033, time 0.6358
Val 61/300, loss 1.3929, time 0.0752 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 62/300, loss 0.0006, time 0.6324
Val 62/300, loss 1.5456, time 0.0751 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 63/300, loss 0.0049, time 0.6360
Val 63/300, loss 1.5784, time 0.0741 | acc 0.7966 | pre 0.8158 | recall 0.8611 | f1 0.8378
Train 64/300, loss 0.0184, time 0.6288
Val 64/300, loss 1.5023, time 0.0747 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 65/300, loss 0.0531, time 0.6317
Val 65/300, loss 1.9066, time 0.0752 | acc 0.6949 | pre 0.6800 | recall 0.9444 | f1 0.7907
Train 66/300, loss 0.0252, time 0.6354
Val 66/300, loss 0.7852, time 0.0736 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 67/300, loss 0.0375, time 0.6296
Val 67/300, loss 0.8973, time 0.0750 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 68/300, loss 0.0253, time 0.6410
Val 68/300, loss 1.3069, time 0.0757 | acc 0.7966 | pre 0.7857 | recall 0.9167 | f1 0.8462
Train 69/300, loss 0.0473, time 0.6292
Val 69/300, loss 1.2580, time 0.0735 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 70/300, loss 0.0172, time 0.6393
Val 70/300, loss 1.1226, time 0.0751 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 71/300, loss 0.0081, time 0.6350
Val 71/300, loss 1.0603, time 0.0755 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 72/300, loss 0.0109, time 0.6431
Val 72/300, loss 1.0667, time 0.0755 | acc 0.8136 | pre 0.8378 | recall 0.8611 | f1 0.8493
Train 73/300, loss 0.0199, time 0.6493
Val 73/300, loss 1.0632, time 0.0756 | acc 0.8305 | pre 0.8421 | recall 0.8889 | f1 0.8649
Train 74/300, loss 0.0145, time 0.6319
Val 74/300, loss 1.0944, time 0.0753 | acc 0.8305 | pre 0.8421 | recall 0.8889 | f1 0.8649
Train 75/300, loss 0.0041, time 0.6390
Val 75/300, loss 1.1561, time 0.0755 | acc 0.8475 | pre 0.8649 | recall 0.8889 | f1 0.8767
Train 76/300, loss 0.0031, time 0.6407
Val 76/300, loss 1.2105, time 0.0753 | acc 0.8305 | pre 0.8421 | recall 0.8889 | f1 0.8649
Train 77/300, loss 0.0145, time 0.6655
Val 77/300, loss 1.3058, time 0.0756 | acc 0.7966 | pre 0.7857 | recall 0.9167 | f1 0.8462
Train 78/300, loss 0.0048, time 0.6342
Val 78/300, loss 1.1350, time 0.0768 | acc 0.8475 | pre 0.8462 | recall 0.9167 | f1 0.8800
Train 79/300, loss 0.0070, time 0.6380
Val 79/300, loss 1.1095, time 0.0767 | acc 0.8644 | pre 0.8684 | recall 0.9167 | f1 0.8919
Train 80/300, loss 0.0017, time 0.6739
Val 80/300, loss 1.1060, time 0.0781 | acc 0.8475 | pre 0.8649 | recall 0.8889 | f1 0.8767
Train 81/300, loss 0.0034, time 0.6495
Val 81/300, loss 1.1658, time 0.0766 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 82/300, loss 0.0025, time 0.6416
Val 82/300, loss 1.1711, time 0.0790 | acc 0.8136 | pre 0.8049 | recall 0.9167 | f1 0.8571
Train 83/300, loss 0.0022, time 0.6358
Val 83/300, loss 1.2111, time 0.0759 | acc 0.8136 | pre 0.8049 | recall 0.9167 | f1 0.8571
Train 84/300, loss 0.0020, time 0.6432
Val 84/300, loss 1.2581, time 0.0768 | acc 0.8305 | pre 0.8250 | recall 0.9167 | f1 0.8684
Train 85/300, loss 0.0011, time 0.6462
Val 85/300, loss 1.2640, time 0.0768 | acc 0.8136 | pre 0.8049 | recall 0.9167 | f1 0.8571
Train 86/300, loss 0.0005, time 0.6410
Val 86/300, loss 1.2456, time 0.0768 | acc 0.8136 | pre 0.8049 | recall 0.9167 | f1 0.8571
Train 87/300, loss 0.0008, time 0.6628
Val 87/300, loss 1.2401, time 0.0768 | acc 0.8136 | pre 0.8049 | recall 0.9167 | f1 0.8571
Train 88/300, loss 0.0007, time 0.6477
Val 88/300, loss 1.2530, time 0.0771 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 89/300, loss 0.0006, time 0.6550
Val 89/300, loss 1.2719, time 0.0768 | acc 0.8305 | pre 0.8250 | recall 0.9167 | f1 0.8684
Train 90/300, loss 0.0013, time 0.6489
Val 90/300, loss 1.3139, time 0.0767 | acc 0.8136 | pre 0.8049 | recall 0.9167 | f1 0.8571
Train 91/300, loss 0.0007, time 0.6496
Val 91/300, loss 1.2813, time 0.0767 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 92/300, loss 0.0055, time 0.6372
Val 92/300, loss 1.2436, time 0.0766 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 93/300, loss 0.0022, time 0.6419
Val 93/300, loss 1.4341, time 0.0765 | acc 0.8136 | pre 0.8049 | recall 0.9167 | f1 0.8571
Train 94/300, loss 0.0024, time 0.6532
Val 94/300, loss 1.5321, time 0.0769 | acc 0.8136 | pre 0.8049 | recall 0.9167 | f1 0.8571
Train 95/300, loss 0.0127, time 0.6419
Val 95/300, loss 1.4631, time 0.0769 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 96/300, loss 0.0125, time 0.6396
Val 96/300, loss 1.5071, time 0.0763 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 97/300, loss 0.0057, time 0.6447
Val 97/300, loss 1.6462, time 0.0763 | acc 0.7288 | pre 0.7174 | recall 0.9167 | f1 0.8049
Train 98/300, loss 0.0232, time 0.6453
Val 98/300, loss 1.3916, time 0.0764 | acc 0.8305 | pre 0.8250 | recall 0.9167 | f1 0.8684
Train 99/300, loss 0.0170, time 0.6480
Val 99/300, loss 1.4559, time 0.0768 | acc 0.8136 | pre 0.8049 | recall 0.9167 | f1 0.8571
Train 100/300, loss 0.0057, time 0.6547
Val 100/300, loss 1.5157, time 0.0768 | acc 0.7966 | pre 0.7857 | recall 0.9167 | f1 0.8462
Train 101/300, loss 0.0027, time 0.6380
Val 101/300, loss 1.4175, time 0.0768 | acc 0.8475 | pre 0.8462 | recall 0.9167 | f1 0.8800
Train 102/300, loss 0.0016, time 0.6412
Val 102/300, loss 1.4010, time 0.0768 | acc 0.8305 | pre 0.8421 | recall 0.8889 | f1 0.8649
Train 103/300, loss 0.0083, time 0.6507
Val 103/300, loss 1.3032, time 0.0770 | acc 0.8136 | pre 0.8049 | recall 0.9167 | f1 0.8571
Train 104/300, loss 0.0031, time 0.6489
Val 104/300, loss 1.3513, time 0.0784 | acc 0.8136 | pre 0.8049 | recall 0.9167 | f1 0.8571
Train 105/300, loss 0.0015, time 0.6431
Val 105/300, loss 1.4026, time 0.0765 | acc 0.7966 | pre 0.7857 | recall 0.9167 | f1 0.8462
Train 106/300, loss 0.0051, time 0.6408
Val 106/300, loss 1.3961, time 0.0772 | acc 0.8136 | pre 0.8049 | recall 0.9167 | f1 0.8571
Train 107/300, loss 0.0007, time 0.7125
Val 107/300, loss 1.4430, time 0.0734 | acc 0.7966 | pre 0.7857 | recall 0.9167 | f1 0.8462
Train 108/300, loss 0.0099, time 0.6272
Val 108/300, loss 1.4838, time 0.0769 | acc 0.7966 | pre 0.7857 | recall 0.9167 | f1 0.8462
Train 109/300, loss 0.0015, time 0.6934
Val 109/300, loss 1.3908, time 0.0738 | acc 0.7966 | pre 0.7857 | recall 0.9167 | f1 0.8462
Train 110/300, loss 0.0018, time 0.6299
Val 110/300, loss 1.3913, time 0.0764 | acc 0.7966 | pre 0.7857 | recall 0.9167 | f1 0.8462
Train 111/300, loss 0.0004, time 0.6975
Val 111/300, loss 1.3189, time 0.0723 | acc 0.8475 | pre 0.8462 | recall 0.9167 | f1 0.8800
Train 112/300, loss 0.0011, time 0.6078
Val 112/300, loss 1.3893, time 0.0748 | acc 0.8305 | pre 0.8250 | recall 0.9167 | f1 0.8684
Train 113/300, loss 0.0045, time 0.7190
Val 113/300, loss 1.4223, time 0.0720 | acc 0.8136 | pre 0.8049 | recall 0.9167 | f1 0.8571
Train 114/300, loss 0.0015, time 0.6298
Val 114/300, loss 1.4220, time 0.0753 | acc 0.8305 | pre 0.8250 | recall 0.9167 | f1 0.8684
Train 115/300, loss 0.0049, time 0.6418
Val 115/300, loss 1.3494, time 0.0720 | acc 0.8305 | pre 0.8250 | recall 0.9167 | f1 0.8684
Train 116/300, loss 0.0026, time 0.6200
Val 116/300, loss 1.2657, time 0.0759 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 117/300, loss 0.0007, time 0.6454
Val 117/300, loss 1.2952, time 0.0798 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 118/300, loss 0.0016, time 0.5548
Val 118/300, loss 1.3374, time 0.0752 | acc 0.8305 | pre 0.8250 | recall 0.9167 | f1 0.8684
Train 119/300, loss 0.0004, time 0.5632
Val 119/300, loss 1.3736, time 0.0758 | acc 0.8305 | pre 0.8250 | recall 0.9167 | f1 0.8684
Train 120/300, loss 0.0020, time 0.5826
Val 120/300, loss 1.4386, time 0.0755 | acc 0.8136 | pre 0.8049 | recall 0.9167 | f1 0.8571
Train 121/300, loss 0.0051, time 0.5567
Val 121/300, loss 1.4150, time 0.0767 | acc 0.8305 | pre 0.8250 | recall 0.9167 | f1 0.8684
Train 122/300, loss 0.0274, time 0.6121
Val 122/300, loss 1.6358, time 0.0737 | acc 0.8475 | pre 0.9091 | recall 0.8333 | f1 0.8696
Train 123/300, loss 0.0102, time 0.6119
Val 123/300, loss 1.4602, time 0.0764 | acc 0.8475 | pre 0.8649 | recall 0.8889 | f1 0.8767
Train 124/300, loss 0.0515, time 0.6719
Val 124/300, loss 1.7967, time 0.0739 | acc 0.8305 | pre 0.8250 | recall 0.9167 | f1 0.8684
Train 125/300, loss 0.0393, time 0.6497
Val 125/300, loss 1.9596, time 0.0784 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 126/300, loss 0.0442, time 0.7124
Val 126/300, loss 1.7924, time 0.0724 | acc 0.7797 | pre 0.7447 | recall 0.9722 | f1 0.8434
Train 127/300, loss 0.1159, time 0.6318
Val 127/300, loss 2.2447, time 0.0776 | acc 0.6441 | pre 0.8000 | recall 0.5556 | f1 0.6557
Train 128/300, loss 0.0786, time 0.7100
Val 128/300, loss 2.2726, time 0.0742 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 129/300, loss 0.1770, time 0.6364
Val 129/300, loss 1.6135, time 0.0773 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 130/300, loss 0.0324, time 0.7127
Val 130/300, loss 1.3786, time 0.0734 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 131/300, loss 0.0521, time 0.6199
Val 131/300, loss 1.2475, time 0.0767 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 132/300, loss 0.0296, time 0.6685
Val 132/300, loss 1.1765, time 0.0750 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 133/300, loss 0.0133, time 0.6146
Val 133/300, loss 1.2316, time 0.0777 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 134/300, loss 0.0255, time 0.6486
Val 134/300, loss 1.2276, time 0.0780 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 135/300, loss 0.0133, time 0.6483
Val 135/300, loss 1.4091, time 0.0774 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 136/300, loss 0.0073, time 0.6627
Val 136/300, loss 1.5451, time 0.0781 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 137/300, loss 0.0030, time 0.6666
Val 137/300, loss 1.6009, time 0.0787 | acc 0.7458 | pre 0.7561 | recall 0.8611 | f1 0.8052
Train 138/300, loss 0.0076, time 0.6641
Val 138/300, loss 1.5966, time 0.0787 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 139/300, loss 0.0033, time 0.6541
Val 139/300, loss 1.5494, time 0.0781 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 140/300, loss 0.0036, time 0.6485
Val 140/300, loss 1.6070, time 0.0780 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 141/300, loss 0.0045, time 0.6545
Val 141/300, loss 1.6439, time 0.0781 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 142/300, loss 0.0135, time 0.6511
Val 142/300, loss 1.6684, time 0.0772 | acc 0.7458 | pre 0.7442 | recall 0.8889 | f1 0.8101
Train 143/300, loss 0.0067, time 0.6597
Val 143/300, loss 1.6192, time 0.0781 | acc 0.7966 | pre 0.7857 | recall 0.9167 | f1 0.8462
Train 144/300, loss 0.0027, time 0.6558
Val 144/300, loss 1.5478, time 0.0785 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 145/300, loss 0.0014, time 0.6502
Val 145/300, loss 1.6453, time 0.0780 | acc 0.7966 | pre 0.7857 | recall 0.9167 | f1 0.8462
Train 146/300, loss 0.0073, time 0.6581
Val 146/300, loss 1.7171, time 0.0779 | acc 0.7797 | pre 0.7674 | recall 0.9167 | f1 0.8354
Train 147/300, loss 0.0102, time 0.6571
Val 147/300, loss 1.8249, time 0.0780 | acc 0.7458 | pre 0.7333 | recall 0.9167 | f1 0.8148
Train 148/300, loss 0.0006, time 0.6411
Val 148/300, loss 1.5855, time 0.0779 | acc 0.7797 | pre 0.7674 | recall 0.9167 | f1 0.8354
Train 149/300, loss 0.0164, time 0.6585
Val 149/300, loss 1.8693, time 0.0781 | acc 0.7797 | pre 0.7556 | recall 0.9444 | f1 0.8395
Train 150/300, loss 0.0207, time 0.6429
Val 150/300, loss 1.6611, time 0.0783 | acc 0.7797 | pre 0.7674 | recall 0.9167 | f1 0.8354
Train 151/300, loss 0.0186, time 0.6627
Val 151/300, loss 1.4931, time 0.0780 | acc 0.7966 | pre 0.7857 | recall 0.9167 | f1 0.8462
Train 152/300, loss 0.0415, time 0.6466
Val 152/300, loss 1.4786, time 0.0778 | acc 0.8136 | pre 0.8049 | recall 0.9167 | f1 0.8571
Train 153/300, loss 0.0045, time 0.6540
Val 153/300, loss 1.7163, time 0.0780 | acc 0.7797 | pre 0.7674 | recall 0.9167 | f1 0.8354
Train 154/300, loss 0.0055, time 0.6486
Val 154/300, loss 1.8204, time 0.0782 | acc 0.7797 | pre 0.7674 | recall 0.9167 | f1 0.8354
Train 155/300, loss 0.0107, time 0.6701
Val 155/300, loss 1.8300, time 0.0766 | acc 0.7966 | pre 0.7857 | recall 0.9167 | f1 0.8462
Train 156/300, loss 0.0067, time 0.6477
Val 156/300, loss 1.7275, time 0.0764 | acc 0.7966 | pre 0.7857 | recall 0.9167 | f1 0.8462
Train 157/300, loss 0.0020, time 0.6436
Val 157/300, loss 1.5179, time 0.0769 | acc 0.7966 | pre 0.7857 | recall 0.9167 | f1 0.8462
Train 158/300, loss 0.0066, time 0.6405
Val 158/300, loss 1.4583, time 0.0764 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 159/300, loss 0.0036, time 0.6389
Val 159/300, loss 1.4829, time 0.0762 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 160/300, loss 0.0025, time 0.6362
Val 160/300, loss 1.3921, time 0.0748 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 161/300, loss 0.0042, time 0.6341
Val 161/300, loss 1.4202, time 0.0746 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 162/300, loss 0.0040, time 0.6354
Val 162/300, loss 1.4144, time 0.0745 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 163/300, loss 0.0026, time 0.6333
Val 163/300, loss 1.5074, time 0.0731 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 164/300, loss 0.0008, time 0.6218
Val 164/300, loss 1.6509, time 0.0747 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 165/300, loss 0.0010, time 0.6334
Val 165/300, loss 1.7064, time 0.0750 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 166/300, loss 0.0010, time 0.6279
Val 166/300, loss 1.7338, time 0.0749 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 167/300, loss 0.0017, time 0.6425
Val 167/300, loss 1.7254, time 0.0749 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 168/300, loss 0.0004, time 0.6446
Val 168/300, loss 1.7007, time 0.0742 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 169/300, loss 0.0006, time 0.6312
Val 169/300, loss 1.7397, time 0.0750 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 170/300, loss 0.0017, time 0.6309
Val 170/300, loss 1.7753, time 0.0749 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 171/300, loss 0.0005, time 0.6358
Val 171/300, loss 1.8088, time 0.0747 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 172/300, loss 0.0007, time 0.6286
Val 172/300, loss 1.8485, time 0.0748 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 173/300, loss 0.0006, time 0.6358
Val 173/300, loss 1.8620, time 0.0736 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 174/300, loss 0.0004, time 0.6407
Val 174/300, loss 1.8842, time 0.0752 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 175/300, loss 0.0031, time 0.6338
Val 175/300, loss 1.9465, time 0.0755 | acc 0.7627 | pre 0.7500 | recall 0.9167 | f1 0.8250
Train 176/300, loss 0.0067, time 0.6305
Val 176/300, loss 1.9002, time 0.0752 | acc 0.7458 | pre 0.7442 | recall 0.8889 | f1 0.8101
Train 177/300, loss 0.0003, time 0.6470
Val 177/300, loss 1.7943, time 0.0766 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 178/300, loss 0.0014, time 0.6419
Val 178/300, loss 1.6530, time 0.0769 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 179/300, loss 0.0006, time 0.6429
Val 179/300, loss 1.6486, time 0.0770 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 180/300, loss 0.0003, time 0.6412
Val 180/300, loss 1.6429, time 0.0776 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 181/300, loss 0.0006, time 0.6421
Val 181/300, loss 1.5732, time 0.0767 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 182/300, loss 0.0018, time 0.6374
Val 182/300, loss 1.6283, time 0.0768 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 183/300, loss 0.0009, time 0.6335
Val 183/300, loss 1.6135, time 0.0766 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 184/300, loss 0.0002, time 0.6452
Val 184/300, loss 1.6246, time 0.0765 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 185/300, loss 0.0036, time 0.6423
Val 185/300, loss 1.6648, time 0.0766 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 186/300, loss 0.0002, time 0.6379
Val 186/300, loss 1.6793, time 0.0766 | acc 0.8305 | pre 0.8421 | recall 0.8889 | f1 0.8649
Train 187/300, loss 0.0003, time 0.6366
Val 187/300, loss 1.6724, time 0.0766 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 188/300, loss 0.0005, time 0.6417
Val 188/300, loss 1.6523, time 0.0769 | acc 0.8136 | pre 0.8205 | recall 0.8889 | f1 0.8533
Train 189/300, loss 0.0031, time 0.6602
Val 189/300, loss 1.7202, time 0.0771 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 190/300, loss 0.0015, time 0.6478
Val 190/300, loss 1.6947, time 0.0769 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 191/300, loss 0.0006, time 0.6656
Val 191/300, loss 1.6711, time 0.0748 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 192/300, loss 0.0002, time 0.6328
Val 192/300, loss 1.6241, time 0.0770 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 193/300, loss 0.0006, time 0.6635
Val 193/300, loss 1.5932, time 0.0744 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 194/300, loss 0.0002, time 0.6371
Val 194/300, loss 1.5905, time 0.0765 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 195/300, loss 0.0001, time 0.6322
Val 195/300, loss 1.5853, time 0.0752 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 196/300, loss 0.0001, time 0.6445
Val 196/300, loss 1.5687, time 0.0773 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 197/300, loss 0.0019, time 0.6614
Val 197/300, loss 1.6015, time 0.0754 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 198/300, loss 0.0002, time 0.7090
Val 198/300, loss 1.6862, time 0.0769 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 199/300, loss 0.0003, time 0.6333
Val 199/300, loss 1.7460, time 0.0738 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 200/300, loss 0.0011, time 0.6294
Val 200/300, loss 1.7466, time 0.0754 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 201/300, loss 0.0002, time 0.6260
Val 201/300, loss 1.7427, time 0.0735 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 202/300, loss 0.0001, time 0.6234
Val 202/300, loss 1.8010, time 0.0902 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 203/300, loss 0.0006, time 0.6924
Val 203/300, loss 1.8512, time 0.0748 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 204/300, loss 0.0001, time 0.6568
Val 204/300, loss 1.8300, time 0.0789 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 205/300, loss 0.0001, time 0.6527
Val 205/300, loss 1.8460, time 0.0762 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 206/300, loss 0.0002, time 0.6332
Val 206/300, loss 1.8619, time 0.0773 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 207/300, loss 0.0001, time 0.6524
Val 207/300, loss 1.8381, time 0.0758 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 208/300, loss 0.0003, time 0.6407
Val 208/300, loss 1.8418, time 0.0769 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 209/300, loss 0.0002, time 0.6958
Val 209/300, loss 1.8398, time 0.0736 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 210/300, loss 0.0005, time 0.6047
Val 210/300, loss 1.8764, time 0.0764 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 211/300, loss 0.0001, time 0.6665
Val 211/300, loss 1.8125, time 0.0738 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 212/300, loss 0.0004, time 0.6401
Val 212/300, loss 1.8481, time 0.0767 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 213/300, loss 0.0003, time 0.6466
Val 213/300, loss 1.8550, time 0.1084 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 214/300, loss 0.0001, time 0.6460
Val 214/300, loss 1.8339, time 0.0791 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 215/300, loss 0.0001, time 0.6404
Val 215/300, loss 1.8709, time 0.1640 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 216/300, loss 0.0001, time 0.6229
Val 216/300, loss 1.8539, time 0.0764 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 217/300, loss 0.0001, time 0.6366
Val 217/300, loss 1.8908, time 0.0764 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 218/300, loss 0.0013, time 0.6273
Val 218/300, loss 1.8978, time 0.0771 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 219/300, loss 0.0001, time 0.6405
Val 219/300, loss 1.9166, time 0.0767 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 220/300, loss 0.0010, time 0.6470
Val 220/300, loss 1.9382, time 0.0767 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 221/300, loss 0.0002, time 0.6384
Val 221/300, loss 1.9825, time 0.0768 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 222/300, loss 0.0002, time 0.6354
Val 222/300, loss 2.0552, time 0.0767 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 223/300, loss 0.0005, time 0.6373
Val 223/300, loss 2.0804, time 0.0766 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 224/300, loss 0.0001, time 0.6395
Val 224/300, loss 2.0318, time 0.0768 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 225/300, loss 0.0004, time 0.6501
Val 225/300, loss 2.0970, time 0.0768 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 226/300, loss 0.0002, time 0.6389
Val 226/300, loss 2.0995, time 0.0771 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 227/300, loss 0.0002, time 0.6356
Val 227/300, loss 2.0689, time 0.0767 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 228/300, loss 0.0002, time 0.6482
Val 228/300, loss 2.1150, time 0.0768 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 229/300, loss 0.0001, time 0.6376
Val 229/300, loss 2.1060, time 0.0767 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 230/300, loss 0.0003, time 0.6443
Val 230/300, loss 2.1412, time 0.0770 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 231/300, loss 0.0003, time 0.6377
Val 231/300, loss 2.1904, time 0.0764 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 232/300, loss 0.0000, time 0.6533
Val 232/300, loss 2.0415, time 0.0766 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 233/300, loss 0.0002, time 0.6438
Val 233/300, loss 1.9691, time 0.0768 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 234/300, loss 0.0003, time 0.6541
Val 234/300, loss 2.0389, time 0.0769 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 235/300, loss 0.0001, time 0.6430
Val 235/300, loss 1.9904, time 0.0769 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 236/300, loss 0.0001, time 0.6460
Val 236/300, loss 1.9590, time 0.0768 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 237/300, loss 0.0000, time 0.6361
Val 237/300, loss 1.9542, time 0.0768 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 238/300, loss 0.0002, time 0.6492
Val 238/300, loss 1.9586, time 0.0767 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 239/300, loss 0.0001, time 0.6365
Val 239/300, loss 1.9956, time 0.0769 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 240/300, loss 0.0001, time 0.6470
Val 240/300, loss 2.0031, time 0.0771 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 241/300, loss 0.0005, time 0.6389
Val 241/300, loss 1.9452, time 0.0770 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 242/300, loss 0.0001, time 0.6510
Val 242/300, loss 1.9361, time 0.0768 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 243/300, loss 0.0001, time 0.6361
Val 243/300, loss 1.9276, time 0.0768 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 244/300, loss 0.0001, time 0.6385
Val 244/300, loss 1.9482, time 0.0775 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 245/300, loss 0.0000, time 0.6413
Val 245/300, loss 1.9509, time 0.0768 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 246/300, loss 0.0001, time 0.6409
Val 246/300, loss 2.0025, time 0.0768 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 247/300, loss 0.0001, time 0.6532
Val 247/300, loss 1.9716, time 0.0772 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 248/300, loss 0.0000, time 0.6397
Val 248/300, loss 1.9598, time 0.0767 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 249/300, loss 0.0000, time 0.6342
Val 249/300, loss 1.9380, time 0.0767 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 250/300, loss 0.0001, time 0.6593
Val 250/300, loss 1.9428, time 0.0769 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 251/300, loss 0.0001, time 0.6413
Val 251/300, loss 1.9253, time 0.0756 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 252/300, loss 0.0000, time 0.6346
Val 252/300, loss 1.9456, time 0.0766 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 253/300, loss 0.0012, time 0.6457
Val 253/300, loss 2.0919, time 0.0765 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 254/300, loss 0.0001, time 0.6377
Val 254/300, loss 2.0397, time 0.0767 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 255/300, loss 0.0034, time 0.6395
Val 255/300, loss 2.2229, time 0.0766 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 256/300, loss 0.0205, time 0.6363
Val 256/300, loss 2.3679, time 0.0767 | acc 0.7966 | pre 0.7727 | recall 0.9444 | f1 0.8500
Train 257/300, loss 0.0384, time 0.6431
Val 257/300, loss 3.0188, time 0.0767 | acc 0.6949 | pre 0.8214 | recall 0.6389 | f1 0.7187
Train 258/300, loss 0.1809, time 0.6369
Val 258/300, loss 1.9434, time 0.0769 | acc 0.8305 | pre 0.8095 | recall 0.9444 | f1 0.8718
Train 259/300, loss 0.0416, time 0.6337
Val 259/300, loss 1.9757, time 0.0767 | acc 0.7797 | pre 0.7556 | recall 0.9444 | f1 0.8395
Train 260/300, loss 0.0963, time 0.6443
Val 260/300, loss 2.0135, time 0.0767 | acc 0.7458 | pre 0.7234 | recall 0.9444 | f1 0.8193
Train 261/300, loss 0.2159, time 0.6392
Val 261/300, loss 1.9212, time 0.0768 | acc 0.6949 | pre 0.8214 | recall 0.6389 | f1 0.7187
Train 262/300, loss 0.0789, time 0.6395
Val 262/300, loss 1.9188, time 0.0771 | acc 0.6780 | pre 0.7297 | recall 0.7500 | f1 0.7397
Train 263/300, loss 0.0892, time 0.6421
Val 263/300, loss 1.7770, time 0.0766 | acc 0.7627 | pre 0.7750 | recall 0.8611 | f1 0.8158
Train 264/300, loss 0.0508, time 0.6459
Val 264/300, loss 1.8620, time 0.0766 | acc 0.7966 | pre 0.7727 | recall 0.9444 | f1 0.8500
Train 265/300, loss 0.0513, time 0.6408
Val 265/300, loss 1.6524, time 0.0764 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 266/300, loss 0.0463, time 0.6437
Val 266/300, loss 1.9022, time 0.0768 | acc 0.6780 | pre 0.7576 | recall 0.6944 | f1 0.7246
Train 267/300, loss 0.0514, time 0.6554
Val 267/300, loss 1.6214, time 0.0775 | acc 0.7458 | pre 0.8182 | recall 0.7500 | f1 0.7826
Train 268/300, loss 0.0573, time 0.6469
Val 268/300, loss 1.7699, time 0.0771 | acc 0.7458 | pre 0.7561 | recall 0.8611 | f1 0.8052
Train 269/300, loss 0.0264, time 0.6536
Val 269/300, loss 1.8151, time 0.0770 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 270/300, loss 0.0244, time 0.6400
Val 270/300, loss 1.9085, time 0.0773 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 271/300, loss 0.1250, time 0.6481
Val 271/300, loss 1.5708, time 0.0771 | acc 0.7458 | pre 0.7333 | recall 0.9167 | f1 0.8148
Train 272/300, loss 0.0502, time 0.6394
Val 272/300, loss 1.5756, time 0.0768 | acc 0.7458 | pre 0.7333 | recall 0.9167 | f1 0.8148
Train 273/300, loss 0.0759, time 0.6367
Val 273/300, loss 1.5580, time 0.1779 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 274/300, loss 0.0285, time 0.6221
Val 274/300, loss 1.1670, time 0.0764 | acc 0.7458 | pre 0.7692 | recall 0.8333 | f1 0.8000
Train 275/300, loss 0.0284, time 0.5939
Val 275/300, loss 1.2225, time 0.0766 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 276/300, loss 0.0144, time 0.6883
Val 276/300, loss 1.4848, time 0.0759 | acc 0.7627 | pre 0.7500 | recall 0.9167 | f1 0.8250
Train 277/300, loss 0.0257, time 0.6289
Val 277/300, loss 1.7164, time 0.0760 | acc 0.7458 | pre 0.7442 | recall 0.8889 | f1 0.8101
Train 278/300, loss 0.0127, time 0.6508
Val 278/300, loss 1.6988, time 0.0738 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 279/300, loss 0.0038, time 0.6853
Val 279/300, loss 1.6221, time 0.0737 | acc 0.7458 | pre 0.7442 | recall 0.8889 | f1 0.8101
Train 280/300, loss 0.0049, time 0.6424
Val 280/300, loss 1.7280, time 0.0741 | acc 0.7458 | pre 0.7442 | recall 0.8889 | f1 0.8101
Train 281/300, loss 0.0077, time 0.6409
Val 281/300, loss 1.8118, time 0.0752 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 282/300, loss 0.0044, time 0.6207
Val 282/300, loss 1.8598, time 0.0735 | acc 0.7458 | pre 0.7442 | recall 0.8889 | f1 0.8101
Train 283/300, loss 0.0033, time 0.6025
Val 283/300, loss 1.8683, time 0.0752 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 284/300, loss 0.0018, time 0.6840
Val 284/300, loss 1.8122, time 0.0743 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 285/300, loss 0.0063, time 0.6281
Val 285/300, loss 1.8348, time 0.0755 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 286/300, loss 0.0107, time 0.6770
Val 286/300, loss 1.9050, time 0.0748 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 287/300, loss 0.0076, time 0.6416
Val 287/300, loss 2.2110, time 0.0753 | acc 0.7797 | pre 0.7805 | recall 0.8889 | f1 0.8312
Train 288/300, loss 0.0191, time 0.7027
Val 288/300, loss 2.2085, time 0.0720 | acc 0.7458 | pre 0.7333 | recall 0.9167 | f1 0.8148
Train 289/300, loss 0.0056, time 0.6242
Val 289/300, loss 1.9938, time 0.0758 | acc 0.7627 | pre 0.7500 | recall 0.9167 | f1 0.8250
Train 290/300, loss 0.0062, time 0.6897
Val 290/300, loss 1.7692, time 0.0723 | acc 0.7966 | pre 0.7857 | recall 0.9167 | f1 0.8462
Train 291/300, loss 0.0021, time 0.6367
Val 291/300, loss 1.7016, time 0.0763 | acc 0.7966 | pre 0.7857 | recall 0.9167 | f1 0.8462
Train 292/300, loss 0.0022, time 0.7129
Val 292/300, loss 1.6332, time 0.0712 | acc 0.7966 | pre 0.7857 | recall 0.9167 | f1 0.8462
Train 293/300, loss 0.0018, time 0.6074
Val 293/300, loss 1.6053, time 0.0750 | acc 0.7966 | pre 0.7857 | recall 0.9167 | f1 0.8462
Train 294/300, loss 0.0093, time 0.6328
Val 294/300, loss 1.5671, time 0.0729 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 295/300, loss 0.0278, time 0.6149
Val 295/300, loss 1.5255, time 0.0754 | acc 0.7797 | pre 0.7949 | recall 0.8611 | f1 0.8267
Train 296/300, loss 0.0330, time 0.6433
Val 296/300, loss 1.6698, time 0.0743 | acc 0.7119 | pre 0.7714 | recall 0.7500 | f1 0.7606
Train 297/300, loss 0.0118, time 0.6491
Val 297/300, loss 1.8316, time 0.0773 | acc 0.7627 | pre 0.7895 | recall 0.8333 | f1 0.8108
Train 298/300, loss 0.0064, time 0.6991
Val 298/300, loss 2.0144, time 0.0744 | acc 0.7966 | pre 0.8000 | recall 0.8889 | f1 0.8421
Train 299/300, loss 0.0278, time 0.5555
Val 299/300, loss 2.2033, time 0.0755 | acc 0.7627 | pre 0.7619 | recall 0.8889 | f1 0.8205
Train 300/300, loss 0.0070, time 0.6018
Val 300/300, loss 2.1727, time 0.0761 | acc 0.7458 | pre 0.7442 | recall 0.8889 | f1 0.8101
best epoch: 47 acc: 0.8644 | Precision: 0.8889 | recall 0.8889 | f1 0.8889
Total time: 216.5004
Fold 5 / 5
GraphTransformer(
(embedding): Linear(in_features=4096, out_features=256, bias=False)
(encoder): GraphTransformerEncoder(
(layers): ModuleList(
(0-2): 3 x TransformerEncoderLayer(
(self_attn): Attention()
(linear1): Linear(in_features=256, out_features=128, bias=True)
(dropout): Dropout(p=0.1, inplace=False)
(linear2): Linear(in_features=128, out_features=256, bias=True)
(norm1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(norm2): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(dropout1): Dropout(p=0.1, inplace=False)
(dropout2): Dropout(p=0.1, inplace=False)
)
)
)
(classifier): Sequential(
(0): Linear(in_features=256, out_features=256, bias=True)
(1): ReLU(inplace=True)
(2): Linear(in_features=256, out_features=2, bias=True)
)
)
Total number of parameters: 3096706
Extracting 2-hop subgraphs...
Done!
Extracting 2-hop subgraphs...
Done!
Training...
Train 1/300, loss 0.4835, time 0.6522
Val 1/300, loss 0.6631, time 0.0750 | acc 0.6379 | pre 0.6316 | recall 1.0000 | f1 0.7742
Train 2/300, loss 0.3121, time 0.6362
Val 2/300, loss 0.6460, time 0.0725 | acc 0.8103 | pre 0.9310 | recall 0.7500 | f1 0.8308
Train 3/300, loss 0.1965, time 0.6543
Val 3/300, loss 0.6293, time 0.0740 | acc 0.8276 | pre 0.8095 | recall 0.9444 | f1 0.8718
Train 4/300, loss 0.1861, time 0.6546
Val 4/300, loss 0.5323, time 0.0738 | acc 0.8276 | pre 0.7955 | recall 0.9722 | f1 0.8750
Train 5/300, loss 0.1755, time 0.6524
Val 5/300, loss 0.4695, time 0.0736 | acc 0.8276 | pre 0.7955 | recall 0.9722 | f1 0.8750
Train 6/300, loss 0.1465, time 0.6537
Val 6/300, loss 0.4459, time 0.0739 | acc 0.8621 | pre 0.9118 | recall 0.8611 | f1 0.8857
Train 7/300, loss 0.1312, time 0.6545
Val 7/300, loss 0.3062, time 0.0741 | acc 0.8966 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 8/300, loss 0.1037, time 0.6577
Val 8/300, loss 0.2562, time 0.0724 | acc 0.9138 | pre 0.8780 | recall 1.0000 | f1 0.9351
Train 9/300, loss 0.1048, time 0.6461
Val 9/300, loss 0.2191, time 0.0724 | acc 0.8966 | pre 0.8750 | recall 0.9722 | f1 0.9211
Train 10/300, loss 0.1419, time 0.6463
Val 10/300, loss 0.1883, time 0.0723 | acc 0.9310 | pre 0.9444 | recall 0.9444 | f1 0.9444
Train 11/300, loss 0.1281, time 0.6461
Val 11/300, loss 0.3832, time 0.0724 | acc 0.8103 | pre 0.9032 | recall 0.7778 | f1 0.8358
Train 12/300, loss 0.1042, time 0.6645
Val 12/300, loss 0.4385, time 0.0724 | acc 0.8448 | pre 0.8462 | recall 0.9167 | f1 0.8800
Train 13/300, loss 0.0894, time 0.6492
Val 13/300, loss 0.2932, time 0.0722 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 14/300, loss 0.0425, time 0.6538
Val 14/300, loss 0.3591, time 0.0722 | acc 0.8621 | pre 0.9375 | recall 0.8333 | f1 0.8824
Train 15/300, loss 0.0596, time 0.6376
Val 15/300, loss 0.3246, time 0.0708 | acc 0.9138 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 16/300, loss 0.0704, time 0.6451
Val 16/300, loss 1.4923, time 0.0741 | acc 0.7241 | pre 0.6923 | recall 1.0000 | f1 0.8182
Train 17/300, loss 0.0581, time 0.6599
Val 17/300, loss 1.1363, time 0.0709 | acc 0.8103 | pre 0.7660 | recall 1.0000 | f1 0.8675
Train 18/300, loss 0.0411, time 0.6484
Val 18/300, loss 0.4307, time 0.0707 | acc 0.9138 | pre 0.8780 | recall 1.0000 | f1 0.9351
Train 19/300, loss 0.0761, time 0.6422
Val 19/300, loss 0.3006, time 0.0723 | acc 0.9138 | pre 0.8974 | recall 0.9722 | f1 0.9333
Train 20/300, loss 0.0482, time 0.6471
Val 20/300, loss 0.3425, time 0.0723 | acc 0.9138 | pre 0.8974 | recall 0.9722 | f1 0.9333
Train 21/300, loss 0.0392, time 0.6450
Val 21/300, loss 0.2664, time 0.0722 | acc 0.9138 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 22/300, loss 0.0430, time 0.6463
Val 22/300, loss 0.3787, time 0.0727 | acc 0.8793 | pre 0.8718 | recall 0.9444 | f1 0.9067
Train 23/300, loss 0.0366, time 0.6450
Val 23/300, loss 0.3808, time 0.0723 | acc 0.8966 | pre 0.8947 | recall 0.9444 | f1 0.9189
Train 24/300, loss 0.0653, time 0.6396
Val 24/300, loss 0.3140, time 0.0723 | acc 0.8966 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 25/300, loss 0.0243, time 0.6405
Val 25/300, loss 0.2928, time 0.0707 | acc 0.8966 | pre 0.8750 | recall 0.9722 | f1 0.9211
Train 26/300, loss 0.0279, time 0.6414
Val 26/300, loss 0.3601, time 0.0707 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 27/300, loss 0.0154, time 0.6428
Val 27/300, loss 0.3339, time 0.0711 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 28/300, loss 0.0133, time 0.6406
Val 28/300, loss 0.2698, time 0.0707 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 29/300, loss 0.0284, time 0.6472
Val 29/300, loss 0.2253, time 0.0710 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 30/300, loss 0.0138, time 0.6416
Val 30/300, loss 0.3207, time 0.0706 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 31/300, loss 0.0097, time 0.6462
Val 31/300, loss 0.3462, time 0.0721 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 32/300, loss 0.0131, time 0.6450
Val 32/300, loss 0.3377, time 0.0707 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 33/300, loss 0.0042, time 0.6463
Val 33/300, loss 0.3978, time 0.0709 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 34/300, loss 0.0060, time 0.6434
Val 34/300, loss 0.4732, time 0.0708 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 35/300, loss 0.0201, time 0.6491
Val 35/300, loss 0.3667, time 0.0709 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 36/300, loss 0.0147, time 0.6485
Val 36/300, loss 0.4151, time 0.0710 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 37/300, loss 0.0067, time 0.6615
Val 37/300, loss 0.4081, time 0.0709 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 38/300, loss 0.0066, time 0.6457
Val 38/300, loss 0.4312, time 0.0707 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 39/300, loss 0.0032, time 0.6487
Val 39/300, loss 0.4786, time 0.0708 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 40/300, loss 0.0049, time 0.6409
Val 40/300, loss 0.4709, time 0.0708 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 41/300, loss 0.0029, time 0.6407
Val 41/300, loss 0.4522, time 0.0710 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 42/300, loss 0.0032, time 0.6452
Val 42/300, loss 0.4573, time 0.0713 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 43/300, loss 0.0017, time 0.6541
Val 43/300, loss 0.4619, time 0.0725 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 44/300, loss 0.0010, time 0.6439
Val 44/300, loss 0.4540, time 0.0710 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 45/300, loss 0.0006, time 0.6491
Val 45/300, loss 0.4516, time 0.0709 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 46/300, loss 0.0039, time 0.6496
Val 46/300, loss 0.4588, time 0.0724 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 47/300, loss 0.0015, time 0.6390
Val 47/300, loss 0.4058, time 0.0710 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 48/300, loss 0.0016, time 0.6510
Val 48/300, loss 0.4510, time 0.0709 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 49/300, loss 0.0020, time 0.6497
Val 49/300, loss 0.5626, time 0.0705 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 50/300, loss 0.0016, time 0.6461
Val 50/300, loss 0.6168, time 0.0707 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 51/300, loss 0.0015, time 0.6427
Val 51/300, loss 0.5638, time 0.0710 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 52/300, loss 0.0003, time 0.6475
Val 52/300, loss 0.5712, time 0.0708 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 53/300, loss 0.0020, time 0.6531
Val 53/300, loss 0.5637, time 0.0726 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 54/300, loss 0.0008, time 0.6468
Val 54/300, loss 0.5464, time 0.0706 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 55/300, loss 0.0012, time 0.6459
Val 55/300, loss 0.5300, time 0.0705 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 56/300, loss 0.0007, time 0.6261
Val 56/300, loss 0.5239, time 0.0722 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 57/300, loss 0.0014, time 0.6446
Val 57/300, loss 0.5044, time 0.0739 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 58/300, loss 0.0005, time 0.6354
Val 58/300, loss 0.5252, time 0.0728 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 59/300, loss 0.0011, time 0.6313
Val 59/300, loss 0.5813, time 0.0736 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 60/300, loss 0.0010, time 0.7208
Val 60/300, loss 0.6036, time 0.0693 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 61/300, loss 0.0054, time 0.6367
Val 61/300, loss 0.6247, time 0.0726 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 62/300, loss 0.0047, time 0.7169
Val 62/300, loss 0.5762, time 0.0721 | acc 0.8966 | pre 0.8947 | recall 0.9444 | f1 0.9189
Train 63/300, loss 0.0043, time 0.6607
Val 63/300, loss 0.5369, time 0.0744 | acc 0.8966 | pre 0.9412 | recall 0.8889 | f1 0.9143
Train 64/300, loss 0.0375, time 0.6393
Val 64/300, loss 0.3765, time 0.0729 | acc 0.9310 | pre 0.9444 | recall 0.9444 | f1 0.9444
Train 65/300, loss 0.0085, time 0.6396
Val 65/300, loss 0.4016, time 0.0735 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 66/300, loss 0.0062, time 0.7104
Val 66/300, loss 0.4879, time 0.0716 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 67/300, loss 0.0030, time 0.6486
Val 67/300, loss 0.4751, time 0.0743 | acc 0.8966 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 68/300, loss 0.0013, time 0.7155
Val 68/300, loss 0.4522, time 0.0705 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 69/300, loss 0.0008, time 0.6323
Val 69/300, loss 0.4632, time 0.0741 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 70/300, loss 0.0013, time 0.7150
Val 70/300, loss 0.4462, time 0.0716 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 71/300, loss 0.0008, time 0.6414
Val 71/300, loss 0.4466, time 0.0742 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 72/300, loss 0.0012, time 0.6849
Val 72/300, loss 0.4620, time 0.0704 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 73/300, loss 0.0003, time 0.6330
Val 73/300, loss 0.4583, time 0.0716 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 74/300, loss 0.0041, time 0.6525
Val 74/300, loss 0.4732, time 0.0699 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 75/300, loss 0.0005, time 0.6360
Val 75/300, loss 0.5171, time 0.0732 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 76/300, loss 0.0169, time 0.6715
Val 76/300, loss 0.3960, time 0.0707 | acc 0.9138 | pre 0.8974 | recall 0.9722 | f1 0.9333
Train 77/300, loss 0.1713, time 0.6214
Val 77/300, loss 0.8441, time 0.0720 | acc 0.8276 | pre 0.9062 | recall 0.8056 | f1 0.8529
Train 78/300, loss 0.1063, time 0.6530
Val 78/300, loss 0.8319, time 0.1385 | acc 0.7931 | pre 0.9615 | recall 0.6944 | f1 0.8065
Train 79/300, loss 0.1287, time 0.6456
Val 79/300, loss 0.5180, time 0.0738 | acc 0.8621 | pre 0.8333 | recall 0.9722 | f1 0.8974
Train 80/300, loss 0.1137, time 0.6558
Val 80/300, loss 1.2296, time 0.0723 | acc 0.7759 | pre 0.7447 | recall 0.9722 | f1 0.8434
Train 81/300, loss 0.0956, time 0.6565
Val 81/300, loss 0.4938, time 0.0742 | acc 0.9310 | pre 0.9000 | recall 1.0000 | f1 0.9474
Train 82/300, loss 0.0465, time 0.6640
Val 82/300, loss 0.3900, time 0.0742 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 83/300, loss 0.0118, time 0.6725
Val 83/300, loss 0.4415, time 0.0741 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 84/300, loss 0.0127, time 0.6469
Val 84/300, loss 0.4802, time 0.0738 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 85/300, loss 0.0172, time 0.6478
Val 85/300, loss 0.5138, time 0.0730 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 86/300, loss 0.0066, time 0.6686
Val 86/300, loss 0.5474, time 0.0739 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 87/300, loss 0.0044, time 0.6516
Val 87/300, loss 0.5075, time 0.0738 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 88/300, loss 0.0421, time 0.6545
Val 88/300, loss 0.5253, time 0.0739 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 89/300, loss 0.0070, time 0.6472
Val 89/300, loss 0.6104, time 0.0738 | acc 0.8966 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 90/300, loss 0.0157, time 0.6523
Val 90/300, loss 0.4945, time 0.0740 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 91/300, loss 0.0386, time 0.6516
Val 91/300, loss 0.5517, time 0.0737 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 92/300, loss 0.0014, time 0.6512
Val 92/300, loss 0.5771, time 0.0709 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 93/300, loss 0.0016, time 0.6458
Val 93/300, loss 0.6004, time 0.0708 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 94/300, loss 0.0068, time 0.6510
Val 94/300, loss 0.6031, time 0.0739 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 95/300, loss 0.0119, time 0.6460
Val 95/300, loss 0.4913, time 0.0724 | acc 0.9483 | pre 0.9231 | recall 1.0000 | f1 0.9600
Train 96/300, loss 0.0110, time 0.6468
Val 96/300, loss 0.3927, time 0.0726 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 97/300, loss 0.0157, time 0.6474
Val 97/300, loss 0.2689, time 0.0725 | acc 0.9310 | pre 0.9444 | recall 0.9444 | f1 0.9444
Train 98/300, loss 0.0047, time 0.6511
Val 98/300, loss 0.2903, time 0.0722 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 99/300, loss 0.0160, time 0.6456
Val 99/300, loss 0.4008, time 0.0724 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 100/300, loss 0.0048, time 0.6393
Val 100/300, loss 0.4149, time 0.0725 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 101/300, loss 0.0047, time 0.6469
Val 101/300, loss 0.4012, time 0.0725 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 102/300, loss 0.0029, time 0.6405
Val 102/300, loss 0.4007, time 0.0726 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 103/300, loss 0.0037, time 0.6419
Val 103/300, loss 0.3988, time 0.0723 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 104/300, loss 0.0013, time 0.6390
Val 104/300, loss 0.3553, time 0.0723 | acc 0.9310 | pre 0.9444 | recall 0.9444 | f1 0.9444
Train 105/300, loss 0.0160, time 0.6406
Val 105/300, loss 0.5109, time 0.0722 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 106/300, loss 0.0075, time 0.6448
Val 106/300, loss 0.7261, time 0.0721 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 107/300, loss 0.0225, time 0.6409
Val 107/300, loss 0.4453, time 0.0722 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 108/300, loss 0.0068, time 0.6438
Val 108/300, loss 0.3908, time 0.0723 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 109/300, loss 0.0128, time 0.6509
Val 109/300, loss 0.4274, time 0.0723 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 110/300, loss 0.0089, time 0.6392
Val 110/300, loss 0.6867, time 0.0723 | acc 0.9310 | pre 0.9000 | recall 1.0000 | f1 0.9474
Train 111/300, loss 0.0032, time 0.6373
Val 111/300, loss 0.6256, time 0.0722 | acc 0.9310 | pre 0.9000 | recall 1.0000 | f1 0.9474
Train 112/300, loss 0.0083, time 0.6459
Val 112/300, loss 0.5059, time 0.0728 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 113/300, loss 0.0096, time 0.6467
Val 113/300, loss 0.4433, time 0.0726 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 114/300, loss 0.0129, time 0.6405
Val 114/300, loss 0.4892, time 0.0724 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 115/300, loss 0.0044, time 0.6424
Val 115/300, loss 0.5749, time 0.0722 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 116/300, loss 0.0254, time 0.6396
Val 116/300, loss 0.4981, time 0.0726 | acc 0.8793 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 117/300, loss 0.0035, time 0.6461
Val 117/300, loss 0.6517, time 0.0725 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 118/300, loss 0.0025, time 0.6448
Val 118/300, loss 0.8106, time 0.0728 | acc 0.9310 | pre 0.9000 | recall 1.0000 | f1 0.9474
Train 119/300, loss 0.0033, time 0.6405
Val 119/300, loss 0.7348, time 0.0724 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 120/300, loss 0.0025, time 0.6496
Val 120/300, loss 0.6928, time 0.0725 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 121/300, loss 0.0005, time 0.6452
Val 121/300, loss 0.6525, time 0.0727 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 122/300, loss 0.0022, time 0.6500
Val 122/300, loss 0.6528, time 0.0722 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 123/300, loss 0.0008, time 0.6457
Val 123/300, loss 0.6451, time 0.0727 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 124/300, loss 0.0005, time 0.6474
Val 124/300, loss 0.6506, time 0.0723 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 125/300, loss 0.0003, time 0.6446
Val 125/300, loss 0.6242, time 0.0725 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 126/300, loss 0.0006, time 0.6503
Val 126/300, loss 0.6302, time 0.0725 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 127/300, loss 0.0002, time 0.6464
Val 127/300, loss 0.6350, time 0.0728 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 128/300, loss 0.0005, time 0.6427
Val 128/300, loss 0.6356, time 0.0728 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 129/300, loss 0.0006, time 0.6437
Val 129/300, loss 0.6682, time 0.0727 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 130/300, loss 0.0003, time 0.6471
Val 130/300, loss 0.6503, time 0.0725 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 131/300, loss 0.0003, time 0.6434
Val 131/300, loss 0.6467, time 0.0727 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 132/300, loss 0.0003, time 0.6457
Val 132/300, loss 0.6301, time 0.0726 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 133/300, loss 0.0002, time 0.6418
Val 133/300, loss 0.6334, time 0.0727 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 134/300, loss 0.0006, time 0.6455
Val 134/300, loss 0.6436, time 0.0727 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 135/300, loss 0.0001, time 0.6488
Val 135/300, loss 0.6399, time 0.0727 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 136/300, loss 0.0003, time 0.6427
Val 136/300, loss 0.6363, time 0.0795 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 137/300, loss 0.0011, time 0.6686
Val 137/300, loss 0.6495, time 0.0726 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 138/300, loss 0.0001, time 0.6451
Val 138/300, loss 0.6406, time 0.0731 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 139/300, loss 0.0005, time 0.6457
Val 139/300, loss 0.6321, time 0.0708 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 140/300, loss 0.0003, time 0.6298
Val 140/300, loss 0.6504, time 0.0711 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 141/300, loss 0.0009, time 0.6088
Val 141/300, loss 0.6543, time 0.0711 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 142/300, loss 0.0015, time 0.6283
Val 142/300, loss 0.6292, time 0.0718 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 143/300, loss 0.0003, time 0.6237
Val 143/300, loss 0.6409, time 0.0707 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 144/300, loss 0.0010, time 0.6281
Val 144/300, loss 0.6370, time 0.0732 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 145/300, loss 0.0005, time 0.6935
Val 145/300, loss 0.6201, time 0.0720 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 146/300, loss 0.0004, time 0.6256
Val 146/300, loss 0.6093, time 0.0725 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 147/300, loss 0.0001, time 0.6419
Val 147/300, loss 0.6147, time 0.0704 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 148/300, loss 0.0017, time 0.6161
Val 148/300, loss 0.6209, time 0.0729 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 149/300, loss 0.0003, time 0.6445
Val 149/300, loss 0.6000, time 0.0690 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 150/300, loss 0.0002, time 0.5639
Val 150/300, loss 0.5953, time 0.0699 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 151/300, loss 0.0002, time 0.6242
Val 151/300, loss 0.5807, time 0.1527 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 152/300, loss 0.0003, time 0.6362
Val 152/300, loss 0.5677, time 0.0701 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 153/300, loss 0.0003, time 0.6129
Val 153/300, loss 0.5926, time 0.0765 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 154/300, loss 0.0004, time 0.6701
Val 154/300, loss 0.5922, time 0.0697 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 155/300, loss 0.0009, time 0.5934
Val 155/300, loss 0.5906, time 0.0711 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 156/300, loss 0.0001, time 0.6336
Val 156/300, loss 0.6387, time 0.0710 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 157/300, loss 0.0062, time 0.5472
Val 157/300, loss 0.5921, time 0.0711 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 158/300, loss 0.0005, time 0.5754
Val 158/300, loss 0.5345, time 0.0701 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 159/300, loss 0.0038, time 0.5591
Val 159/300, loss 0.6743, time 0.0708 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 160/300, loss 0.0003, time 0.6244
Val 160/300, loss 0.7376, time 0.0694 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 161/300, loss 0.0003, time 0.6267
Val 161/300, loss 0.7463, time 0.0708 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 162/300, loss 0.0001, time 0.7057
Val 162/300, loss 0.7078, time 0.0710 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 163/300, loss 0.0002, time 0.6294
Val 163/300, loss 0.6842, time 0.0734 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 164/300, loss 0.0009, time 0.6436
Val 164/300, loss 0.6988, time 0.0731 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 165/300, loss 0.0002, time 0.6411
Val 165/300, loss 0.7240, time 0.0729 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 166/300, loss 0.0002, time 0.6460
Val 166/300, loss 0.6977, time 0.0728 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 167/300, loss 0.0051, time 0.6434
Val 167/300, loss 0.7696, time 0.0734 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 168/300, loss 0.0035, time 0.6414
Val 168/300, loss 0.7333, time 0.0739 | acc 0.9138 | pre 0.8974 | recall 0.9722 | f1 0.9333
Train 169/300, loss 0.0026, time 0.6517
Val 169/300, loss 0.6519, time 0.0733 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 170/300, loss 0.0118, time 0.6543
Val 170/300, loss 0.5579, time 0.0739 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 171/300, loss 0.0008, time 0.6267
Val 171/300, loss 0.6329, time 0.0732 | acc 0.8966 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 172/300, loss 0.0342, time 0.6438
Val 172/300, loss 0.4849, time 0.0731 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 173/300, loss 0.0255, time 0.6327
Val 173/300, loss 0.4260, time 0.0731 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 174/300, loss 0.0055, time 0.6122
Val 174/300, loss 0.4400, time 0.0731 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 175/300, loss 0.0129, time 0.6316
Val 175/300, loss 0.5225, time 0.0730 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 176/300, loss 0.0049, time 0.6171
Val 176/300, loss 0.6096, time 0.0726 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 177/300, loss 0.0342, time 0.6411
Val 177/300, loss 0.7166, time 0.0730 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 178/300, loss 0.0240, time 0.6439
Val 178/300, loss 0.6591, time 0.0731 | acc 0.8966 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 179/300, loss 0.0158, time 0.6465
Val 179/300, loss 0.6550, time 0.0731 | acc 0.8966 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 180/300, loss 0.0031, time 0.6501
Val 180/300, loss 0.6040, time 0.0735 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 181/300, loss 0.0078, time 0.6725
Val 181/300, loss 0.4819, time 0.0732 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 182/300, loss 0.0133, time 0.6462
Val 182/300, loss 0.4932, time 0.0736 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 183/300, loss 0.0242, time 0.6456
Val 183/300, loss 0.6265, time 0.0733 | acc 0.8966 | pre 0.8947 | recall 0.9444 | f1 0.9189
Train 184/300, loss 0.0848, time 0.6492
Val 184/300, loss 0.3761, time 0.0734 | acc 0.9310 | pre 0.9444 | recall 0.9444 | f1 0.9444
Train 185/300, loss 0.0217, time 0.6461
Val 185/300, loss 0.4978, time 0.0732 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 186/300, loss 0.1289, time 0.6509
Val 186/300, loss 0.4679, time 0.0731 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 187/300, loss 0.0387, time 0.6431
Val 187/300, loss 0.5377, time 0.0731 | acc 0.8276 | pre 0.9333 | recall 0.7778 | f1 0.8485
Train 188/300, loss 0.0406, time 0.6529
Val 188/300, loss 0.7764, time 0.0720 | acc 0.8276 | pre 0.9333 | recall 0.7778 | f1 0.8485
Train 189/300, loss 0.0078, time 0.6492
Val 189/300, loss 0.5074, time 0.0734 | acc 0.8793 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 190/300, loss 0.0213, time 0.6568
Val 190/300, loss 0.4359, time 0.0735 | acc 0.8793 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 191/300, loss 0.0030, time 0.6422
Val 191/300, loss 0.3128, time 0.0735 | acc 0.8966 | pre 0.9167 | recall 0.9167 | f1 0.9167
Train 192/300, loss 0.0077, time 0.6504
Val 192/300, loss 0.3205, time 0.0830 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 193/300, loss 0.0025, time 0.6698
Val 193/300, loss 0.3599, time 0.0781 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 194/300, loss 0.0013, time 0.6801
Val 194/300, loss 0.3840, time 0.0727 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 195/300, loss 0.0007, time 0.6511
Val 195/300, loss 0.3874, time 0.0731 | acc 0.9483 | pre 0.9459 | recall 0.9722 | f1 0.9589
Train 196/300, loss 0.0007, time 0.6507
Val 196/300, loss 0.3889, time 0.0732 | acc 0.9483 | pre 0.9459 | recall 0.9722 | f1 0.9589
Train 197/300, loss 0.0013, time 0.6470
Val 197/300, loss 0.3965, time 0.0732 | acc 0.9483 | pre 0.9459 | recall 0.9722 | f1 0.9589
Train 198/300, loss 0.0002, time 0.6460
Val 198/300, loss 0.3826, time 0.0734 | acc 0.9483 | pre 0.9459 | recall 0.9722 | f1 0.9589
Train 199/300, loss 0.0010, time 0.6383
Val 199/300, loss 0.3699, time 0.0732 | acc 0.9483 | pre 0.9459 | recall 0.9722 | f1 0.9589
Train 200/300, loss 0.0012, time 0.6548
Val 200/300, loss 0.3589, time 0.0735 | acc 0.9483 | pre 0.9459 | recall 0.9722 | f1 0.9589
Train 201/300, loss 0.0005, time 0.6413
Val 201/300, loss 0.3642, time 0.0730 | acc 0.9483 | pre 0.9459 | recall 0.9722 | f1 0.9589
Train 202/300, loss 0.0007, time 0.6523
Val 202/300, loss 0.3411, time 0.0732 | acc 0.9483 | pre 0.9459 | recall 0.9722 | f1 0.9589
Train 203/300, loss 0.0007, time 0.6475
Val 203/300, loss 0.3253, time 0.0732 | acc 0.9483 | pre 0.9459 | recall 0.9722 | f1 0.9589
Train 204/300, loss 0.0005, time 0.6432
Val 204/300, loss 0.3140, time 0.0734 | acc 0.9483 | pre 0.9459 | recall 0.9722 | f1 0.9589
Train 205/300, loss 0.0020, time 0.6398
Val 205/300, loss 0.3198, time 0.0702 | acc 0.9483 | pre 0.9459 | recall 0.9722 | f1 0.9589
Train 206/300, loss 0.0008, time 0.6376
Val 206/300, loss 0.3265, time 0.0701 | acc 0.9483 | pre 0.9459 | recall 0.9722 | f1 0.9589
Train 207/300, loss 0.0001, time 0.6408
Val 207/300, loss 0.3259, time 0.0719 | acc 0.9483 | pre 0.9459 | recall 0.9722 | f1 0.9589
Train 208/300, loss 0.0014, time 0.6395
Val 208/300, loss 0.3329, time 0.0706 | acc 0.9483 | pre 0.9459 | recall 0.9722 | f1 0.9589
Train 209/300, loss 0.0014, time 0.6440
Val 209/300, loss 0.3275, time 0.0704 | acc 0.9483 | pre 0.9459 | recall 0.9722 | f1 0.9589
Train 210/300, loss 0.0002, time 0.6397
Val 210/300, loss 0.3157, time 0.0720 | acc 0.9483 | pre 0.9459 | recall 0.9722 | f1 0.9589
Train 211/300, loss 0.0002, time 0.6355
Val 211/300, loss 0.3119, time 0.0701 | acc 0.9483 | pre 0.9459 | recall 0.9722 | f1 0.9589
Train 212/300, loss 0.0001, time 0.6408
Val 212/300, loss 0.3224, time 0.0701 | acc 0.9483 | pre 0.9459 | recall 0.9722 | f1 0.9589
Train 213/300, loss 0.0004, time 0.6388
Val 213/300, loss 0.3179, time 0.0702 | acc 0.9483 | pre 0.9459 | recall 0.9722 | f1 0.9589
Train 214/300, loss 0.0011, time 0.6323
Val 214/300, loss 0.3453, time 0.0702 | acc 0.9483 | pre 0.9459 | recall 0.9722 | f1 0.9589
Train 215/300, loss 0.0009, time 0.6386
Val 215/300, loss 0.3454, time 0.0701 | acc 0.9310 | pre 0.9444 | recall 0.9444 | f1 0.9444
Train 216/300, loss 0.0005, time 0.6481
Val 216/300, loss 0.2910, time 0.0735 | acc 0.9483 | pre 0.9459 | recall 0.9722 | f1 0.9589
Train 217/300, loss 0.0008, time 0.6478
Val 217/300, loss 0.3010, time 0.0732 | acc 0.9483 | pre 0.9459 | recall 0.9722 | f1 0.9589
Train 218/300, loss 0.0004, time 0.6527
Val 218/300, loss 0.3139, time 0.0735 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 219/300, loss 0.0005, time 0.6392
Val 219/300, loss 0.3492, time 0.0734 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 220/300, loss 0.0004, time 0.6621
Val 220/300, loss 0.3541, time 0.0739 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 221/300, loss 0.0001, time 0.6421
Val 221/300, loss 0.3317, time 0.0725 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 222/300, loss 0.0003, time 0.6644
Val 222/300, loss 0.3337, time 0.0737 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 223/300, loss 0.0001, time 0.6354
Val 223/300, loss 0.3108, time 0.0707 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 224/300, loss 0.0001, time 0.6256
Val 224/300, loss 0.3186, time 0.0718 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 225/300, loss 0.0002, time 0.6257
Val 225/300, loss 0.3182, time 0.0703 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 226/300, loss 0.0005, time 0.6159
Val 226/300, loss 0.3237, time 0.0714 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 227/300, loss 0.0002, time 0.6420
Val 227/300, loss 0.3310, time 0.0703 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 228/300, loss 0.0003, time 0.6314
Val 228/300, loss 0.3486, time 0.0718 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 229/300, loss 0.0004, time 0.6290
Val 229/300, loss 0.3504, time 0.0696 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 230/300, loss 0.0002, time 0.6270
Val 230/300, loss 0.3387, time 0.0700 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 231/300, loss 0.0001, time 0.6660
Val 231/300, loss 0.3439, time 0.0711 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 232/300, loss 0.0002, time 0.6307
Val 232/300, loss 0.3422, time 0.0736 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 233/300, loss 0.0001, time 0.6696
Val 233/300, loss 0.3311, time 0.0735 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 234/300, loss 0.0000, time 0.6283
Val 234/300, loss 0.3178, time 0.0735 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 235/300, loss 0.0002, time 0.6502
Val 235/300, loss 0.3266, time 0.1377 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 236/300, loss 0.0002, time 0.6143
Val 236/300, loss 0.3414, time 0.0726 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 237/300, loss 0.0001, time 0.6501
Val 237/300, loss 0.3326, time 0.1750 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 238/300, loss 0.0008, time 0.6185
Val 238/300, loss 0.3428, time 0.0727 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 239/300, loss 0.0001, time 0.6573
Val 239/300, loss 0.4314, time 0.1650 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 240/300, loss 0.0002, time 0.6337
Val 240/300, loss 0.4701, time 0.0727 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 241/300, loss 0.0003, time 0.6365
Val 241/300, loss 0.4682, time 0.0959 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 242/300, loss 0.0001, time 0.6257
Val 242/300, loss 0.4425, time 0.0724 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 243/300, loss 0.0004, time 0.6534
Val 243/300, loss 0.4391, time 0.0806 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 244/300, loss 0.0000, time 0.6195
Val 244/300, loss 0.3823, time 0.0736 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 245/300, loss 0.0002, time 0.6372
Val 245/300, loss 0.3624, time 0.0731 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 246/300, loss 0.0003, time 0.6898
Val 246/300, loss 0.3910, time 0.0771 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 247/300, loss 0.0001, time 0.6178
Val 247/300, loss 0.3815, time 0.0773 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 248/300, loss 0.0001, time 0.6671
Val 248/300, loss 0.3613, time 0.0721 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 249/300, loss 0.0012, time 0.6444
Val 249/300, loss 0.3538, time 0.0755 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 250/300, loss 0.0001, time 0.6456
Val 250/300, loss 0.3848, time 0.0740 | acc 0.9138 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 251/300, loss 0.0088, time 0.6518
Val 251/300, loss 0.3768, time 0.0732 | acc 0.9310 | pre 0.9444 | recall 0.9444 | f1 0.9444
Train 252/300, loss 0.0209, time 0.6505
Val 252/300, loss 0.3175, time 0.0720 | acc 0.9310 | pre 0.9444 | recall 0.9444 | f1 0.9444
Train 253/300, loss 0.0111, time 0.6481
Val 253/300, loss 0.4607, time 0.0731 | acc 0.9483 | pre 0.9231 | recall 1.0000 | f1 0.9600
Train 254/300, loss 0.0222, time 0.6528
Val 254/300, loss 3.4616, time 0.0734 | acc 0.6552 | pre 0.6429 | recall 1.0000 | f1 0.7826
Train 255/300, loss 0.1122, time 0.6501
Val 255/300, loss 1.1863, time 0.0729 | acc 0.7759 | pre 1.0000 | recall 0.6389 | f1 0.7797
Train 256/300, loss 0.1091, time 0.6537
Val 256/300, loss 1.6835, time 0.0732 | acc 0.7414 | pre 1.0000 | recall 0.5833 | f1 0.7368
Train 257/300, loss 0.0590, time 0.6523
Val 257/300, loss 0.6050, time 0.0733 | acc 0.8966 | pre 0.9688 | recall 0.8611 | f1 0.9118
Train 258/300, loss 0.0562, time 0.6497
Val 258/300, loss 0.2624, time 0.0731 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 259/300, loss 0.0321, time 0.6514
Val 259/300, loss 0.4223, time 0.0733 | acc 0.8793 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 260/300, loss 0.0133, time 0.6449
Val 260/300, loss 0.4249, time 0.0730 | acc 0.8793 | pre 0.9143 | recall 0.8889 | f1 0.9014
Train 261/300, loss 0.0046, time 0.6516
Val 261/300, loss 0.2946, time 0.0733 | acc 0.9138 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 262/300, loss 0.0036, time 0.6544
Val 262/300, loss 0.3461, time 0.0730 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 263/300, loss 0.0023, time 0.6500
Val 263/300, loss 0.3760, time 0.0733 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 264/300, loss 0.0098, time 0.6422
Val 264/300, loss 0.4971, time 0.0732 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 265/300, loss 0.0021, time 0.6465
Val 265/300, loss 0.5101, time 0.0730 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 266/300, loss 0.0019, time 0.6547
Val 266/300, loss 0.4497, time 0.0735 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 267/300, loss 0.0013, time 0.6403
Val 267/300, loss 0.4565, time 0.0731 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 268/300, loss 0.0017, time 0.6544
Val 268/300, loss 0.4845, time 0.0731 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 269/300, loss 0.0011, time 0.6350
Val 269/300, loss 0.5092, time 0.0729 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 270/300, loss 0.0016, time 0.6435
Val 270/300, loss 0.5208, time 0.0730 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 271/300, loss 0.0008, time 0.5609
Val 271/300, loss 0.5124, time 0.0712 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 272/300, loss 0.0004, time 0.6103
Val 272/300, loss 0.5104, time 0.0721 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 273/300, loss 0.0018, time 0.6445
Val 273/300, loss 0.4729, time 0.0729 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 274/300, loss 0.0005, time 0.6217
Val 274/300, loss 0.4471, time 0.0727 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 275/300, loss 0.0060, time 0.6386
Val 275/300, loss 0.4590, time 0.0732 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 276/300, loss 0.0008, time 0.6366
Val 276/300, loss 0.4434, time 0.0714 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 277/300, loss 0.0008, time 0.6342
Val 277/300, loss 0.4254, time 0.0724 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 278/300, loss 0.0005, time 0.6014
Val 278/300, loss 0.4365, time 0.0700 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 279/300, loss 0.0003, time 0.6113
Val 279/300, loss 0.4482, time 0.0696 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 280/300, loss 0.0030, time 0.6325
Val 280/300, loss 0.4737, time 0.0694 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 281/300, loss 0.0005, time 0.6278
Val 281/300, loss 0.6014, time 0.0711 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 282/300, loss 0.0027, time 0.6084
Val 282/300, loss 0.5649, time 0.0722 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 283/300, loss 0.0014, time 0.6384
Val 283/300, loss 0.4881, time 0.0711 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 284/300, loss 0.0004, time 0.6295
Val 284/300, loss 0.4521, time 0.0718 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 285/300, loss 0.0003, time 0.6206
Val 285/300, loss 0.4346, time 0.0713 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 286/300, loss 0.0008, time 0.6372
Val 286/300, loss 0.4139, time 0.0720 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 287/300, loss 0.0004, time 0.6411
Val 287/300, loss 0.3914, time 0.0714 | acc 0.9138 | pre 0.9189 | recall 0.9444 | f1 0.9315
Train 288/300, loss 0.0057, time 0.6260
Val 288/300, loss 0.3561, time 0.0720 | acc 0.9310 | pre 0.9444 | recall 0.9444 | f1 0.9444
Train 289/300, loss 0.0007, time 0.6202
Val 289/300, loss 0.3774, time 0.0697 | acc 0.9138 | pre 0.9429 | recall 0.9167 | f1 0.9296
Train 290/300, loss 0.0001, time 0.6291
Val 290/300, loss 0.3926, time 0.0717 | acc 0.9310 | pre 0.9444 | recall 0.9444 | f1 0.9444
Train 291/300, loss 0.0010, time 0.6246
Val 291/300, loss 0.4126, time 0.0712 | acc 0.9310 | pre 0.9444 | recall 0.9444 | f1 0.9444
Train 292/300, loss 0.0001, time 0.6222
Val 292/300, loss 0.4251, time 0.0705 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 293/300, loss 0.0001, time 0.6310
Val 293/300, loss 0.4435, time 0.0712 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 294/300, loss 0.0001, time 0.6221
Val 294/300, loss 0.4382, time 0.0714 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 295/300, loss 0.0001, time 0.6255
Val 295/300, loss 0.4677, time 0.0717 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 296/300, loss 0.0001, time 0.6442
Val 296/300, loss 0.4561, time 0.0731 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 297/300, loss 0.0001, time 0.6410
Val 297/300, loss 0.4670, time 0.0728 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 298/300, loss 0.0001, time 0.6398
Val 298/300, loss 0.4604, time 0.0728 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 299/300, loss 0.0002, time 0.6332
Val 299/300, loss 0.4459, time 0.0727 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
Train 300/300, loss 0.0002, time 0.6430
Val 300/300, loss 0.4495, time 0.0738 | acc 0.9310 | pre 0.9211 | recall 0.9722 | f1 0.9459
best epoch: 94 acc: 0.9483 | Precision: 0.9231 | recall 1.0000 | f1 0.9600
Total time: 215.4082
=================Final Scores: =================
Final mean score: acc: 0.9015195791934542 | Precision: 0.9099893162393162 | recall 0.9333333333333332 | f1 0.9201307189542485
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