Fold 1 / 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 0.4991, 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