lr: 1e-05
sub_13:Test (Best Model) - Loss: 0.6579 - Accuracy: 0.7188 - F1: 0.7163
sub_9:Test (Best Model) - Loss: 0.6590 - Accuracy: 0.6250 - F1: 0.6190
sub_7:Test (Best Model) - Loss: 0.6257 - Accuracy: 0.9375 - F1: 0.9373
sub_24:Test (Best Model) - Loss: 0.6513 - Accuracy: 0.6875 - F1: 0.6825
sub_22:Test (Best Model) - Loss: 0.6625 - Accuracy: 0.7812 - F1: 0.7703
sub_10:Test (Best Model) - Loss: 0.6485 - Accuracy: 0.8438 - F1: 0.8359
sub_29:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.6562 - F1: 0.6476
sub_14:Test (Best Model) - Loss: 0.6808 - Accuracy: 0.6250 - F1: 0.6000
sub_3:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.5312 - F1: 0.5195
sub_12:Test (Best Model) - Loss: 0.6642 - Accuracy: 0.7188 - F1: 0.7163
sub_6:Test (Best Model) - Loss: 0.6633 - Accuracy: 0.6250 - F1: 0.6250
sub_11:Test (Best Model) - Loss: 0.6613 - Accuracy: 0.7273 - F1: 0.7179
sub_28:Test (Best Model) - Loss: 0.6988 - Accuracy: 0.3750 - F1: 0.3522
sub_2:Test (Best Model) - Loss: 0.6919 - Accuracy: 0.4848 - F1: 0.4672
sub_25:Test (Best Model) - Loss: 0.6933 - Accuracy: 0.4848 - F1: 0.4772
sub_16:Test (Best Model) - Loss: 0.6677 - Accuracy: 0.6562 - F1: 0.6476
sub_19:Test (Best Model) - Loss: 0.7228 - Accuracy: 0.4375 - F1: 0.3043
sub_20:Test (Best Model) - Loss: 0.7123 - Accuracy: 0.4375 - F1: 0.3766
sub_21:Test (Best Model) - Loss: 0.6289 - Accuracy: 0.9375 - F1: 0.9352
sub_1:Test (Best Model) - Loss: 0.6588 - Accuracy: 0.7812 - F1: 0.7758
sub_5:Test (Best Model) - Loss: 0.6265 - Accuracy: 0.9688 - F1: 0.9685
sub_4:Test (Best Model) - Loss: 0.6896 - Accuracy: 0.5758 - F1: 0.5754
sub_8:Test (Best Model) - Loss: 0.6975 - Accuracy: 0.4688 - F1: 0.3976
sub_23:Test (Best Model) - Loss: 0.6342 - Accuracy: 0.7879 - F1: 0.7847
sub_15:Test (Best Model) - Loss: 0.6282 - Accuracy: 0.9375 - F1: 0.9365
sub_7:Test (Best Model) - Loss: 0.6690 - Accuracy: 0.6250 - F1: 0.6250
sub_24:Test (Best Model) - Loss: 0.7051 - Accuracy: 0.5000 - F1: 0.4980
sub_13:Test (Best Model) - Loss: 0.6242 - Accuracy: 0.9375 - F1: 0.9373
sub_27:Test (Best Model) - Loss: 0.6150 - Accuracy: 0.9091 - F1: 0.9060
sub_26:Test (Best Model) - Loss: 0.6491 - Accuracy: 0.7576 - F1: 0.7519
sub_17:Test (Best Model) - Loss: 0.6150 - Accuracy: 0.9091 - F1: 0.9060
sub_18:Test (Best Model) - Loss: 0.6088 - Accuracy: 0.9394 - F1: 0.9389
sub_22:Test (Best Model) - Loss: 0.6720 - Accuracy: 0.7500 - F1: 0.7490
sub_24:Test (Best Model) - Loss: 0.6847 - Accuracy: 0.5312 - F1: 0.5077
sub_11:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5152 - F1: 0.4762
sub_29:Test (Best Model) - Loss: 0.6267 - Accuracy: 0.8750 - F1: 0.8704
sub_4:Test (Best Model) - Loss: 0.6607 - Accuracy: 0.7576 - F1: 0.7519
sub_25:Test (Best Model) - Loss: 0.6529 - Accuracy: 0.6970 - F1: 0.6944
sub_9:Test (Best Model) - Loss: 0.6185 - Accuracy: 0.9375 - F1: 0.9373
sub_12:Test (Best Model) - Loss: 0.6367 - Accuracy: 0.8438 - F1: 0.8359
sub_8:Test (Best Model) - Loss: 0.6658 - Accuracy: 0.6875 - F1: 0.6863
sub_1:Test (Best Model) - Loss: 0.6310 - Accuracy: 0.8125 - F1: 0.8118
sub_16:Test (Best Model) - Loss: 0.6907 - Accuracy: 0.4062 - F1: 0.3764
sub_3:Test (Best Model) - Loss: 0.6647 - Accuracy: 0.7500 - F1: 0.7333
sub_23:Test (Best Model) - Loss: 0.6439 - Accuracy: 0.8182 - F1: 0.8167
sub_5:Test (Best Model) - Loss: 0.6612 - Accuracy: 0.4688 - F1: 0.3637
sub_10:Test (Best Model) - Loss: 0.6138 - Accuracy: 1.0000 - F1: 1.0000
sub_21:Test (Best Model) - Loss: 0.6197 - Accuracy: 0.8125 - F1: 0.7922
sub_14:Test (Best Model) - Loss: 0.6571 - Accuracy: 0.7500 - F1: 0.7460
sub_13:Test (Best Model) - Loss: 0.6259 - Accuracy: 0.8750 - F1: 0.8667
sub_15:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.7812 - F1: 0.7703
sub_7:Test (Best Model) - Loss: 0.6000 - Accuracy: 0.9062 - F1: 0.9062
sub_20:Test (Best Model) - Loss: 0.6359 - Accuracy: 0.8750 - F1: 0.8704
sub_27:Test (Best Model) - Loss: 0.6512 - Accuracy: 0.8485 - F1: 0.8462
sub_17:Test (Best Model) - Loss: 0.6512 - Accuracy: 0.8485 - F1: 0.8462
sub_19:Test (Best Model) - Loss: 0.6210 - Accuracy: 0.9062 - F1: 0.9039
sub_28:Test (Best Model) - Loss: 0.7129 - Accuracy: 0.4062 - F1: 0.2889
sub_22:Test (Best Model) - Loss: 0.7191 - Accuracy: 0.3438 - F1: 0.3379
sub_24:Test (Best Model) - Loss: 0.6450 - Accuracy: 0.8125 - F1: 0.8125
sub_26:Test (Best Model) - Loss: 0.6492 - Accuracy: 0.8485 - F1: 0.8485
sub_6:Test (Best Model) - Loss: 0.6698 - Accuracy: 0.5938 - F1: 0.5934
sub_29:Test (Best Model) - Loss: 0.6877 - Accuracy: 0.5312 - F1: 0.5195
sub_11:Test (Best Model) - Loss: 0.7178 - Accuracy: 0.3939 - F1: 0.3182
sub_2:Test (Best Model) - Loss: 0.6535 - Accuracy: 0.7879 - F1: 0.7871
sub_5:Test (Best Model) - Loss: 0.6779 - Accuracy: 0.4688 - F1: 0.3637
sub_18:Test (Best Model) - Loss: 0.6216 - Accuracy: 0.9697 - F1: 0.9696
sub_25:Test (Best Model) - Loss: 0.6886 - Accuracy: 0.4242 - F1: 0.3660
sub_1:Test (Best Model) - Loss: 0.5848 - Accuracy: 1.0000 - F1: 1.0000
sub_10:Test (Best Model) - Loss: 0.6409 - Accuracy: 0.7812 - F1: 0.7810
sub_13:Test (Best Model) - Loss: 0.6095 - Accuracy: 0.9688 - F1: 0.9685
sub_3:Test (Best Model) - Loss: 0.6651 - Accuracy: 0.6562 - F1: 0.6559
sub_4:Test (Best Model) - Loss: 0.5935 - Accuracy: 0.8788 - F1: 0.8759
sub_20:Test (Best Model) - Loss: 0.6441 - Accuracy: 0.7500 - F1: 0.7460
sub_12:Test (Best Model) - Loss: 0.6102 - Accuracy: 0.8438 - F1: 0.8436
sub_9:Test (Best Model) - Loss: 0.6350 - Accuracy: 0.7500 - F1: 0.7460
sub_21:Test (Best Model) - Loss: 0.6536 - Accuracy: 0.5625 - F1: 0.5608
sub_7:Test (Best Model) - Loss: 0.6370 - Accuracy: 0.8438 - F1: 0.8303
sub_19:Test (Best Model) - Loss: 0.6454 - Accuracy: 0.8125 - F1: 0.7922
sub_8:Test (Best Model) - Loss: 0.5691 - Accuracy: 0.9375 - F1: 0.9352
sub_26:Test (Best Model) - Loss: 0.6710 - Accuracy: 0.6364 - F1: 0.6360
sub_23:Test (Best Model) - Loss: 0.6142 - Accuracy: 0.8788 - F1: 0.8787
sub_2:Test (Best Model) - Loss: 0.6164 - Accuracy: 0.8485 - F1: 0.8390
sub_16:Test (Best Model) - Loss: 0.6464 - Accuracy: 0.7812 - F1: 0.7810
sub_15:Test (Best Model) - Loss: 0.6122 - Accuracy: 0.9062 - F1: 0.9062
sub_28:Test (Best Model) - Loss: 0.6040 - Accuracy: 0.8750 - F1: 0.8750
sub_6:Test (Best Model) - Loss: 0.6497 - Accuracy: 0.6875 - F1: 0.6863
sub_24:Test (Best Model) - Loss: 0.6184 - Accuracy: 0.9375 - F1: 0.9373
sub_1:Test (Best Model) - Loss: 0.6372 - Accuracy: 0.8750 - F1: 0.8730
sub_29:Test (Best Model) - Loss: 0.6412 - Accuracy: 0.8438 - F1: 0.8398
sub_17:Test (Best Model) - Loss: 0.6279 - Accuracy: 0.8182 - F1: 0.8167
sub_3:Test (Best Model) - Loss: 0.6226 - Accuracy: 0.9062 - F1: 0.9039
sub_22:Test (Best Model) - Loss: 0.6602 - Accuracy: 0.8125 - F1: 0.8125
sub_27:Test (Best Model) - Loss: 0.6279 - Accuracy: 0.8182 - F1: 0.8167
sub_20:Test (Best Model) - Loss: 0.6496 - Accuracy: 0.7500 - F1: 0.7409
sub_14:Test (Best Model) - Loss: 0.6696 - Accuracy: 0.6250 - F1: 0.5000
sub_5:Test (Best Model) - Loss: 0.5944 - Accuracy: 0.9688 - F1: 0.9680
sub_12:Test (Best Model) - Loss: 0.6089 - Accuracy: 0.9688 - F1: 0.9680
sub_10:Test (Best Model) - Loss: 0.6164 - Accuracy: 0.8438 - F1: 0.8359
sub_11:Test (Best Model) - Loss: 0.6429 - Accuracy: 0.8485 - F1: 0.8390
sub_18:Test (Best Model) - Loss: 0.6034 - Accuracy: 0.9091 - F1: 0.9091
sub_4:Test (Best Model) - Loss: 0.6323 - Accuracy: 0.8788 - F1: 0.8778
sub_2:Test (Best Model) - Loss: 0.6769 - Accuracy: 0.6061 - F1: 0.6046
sub_25:Test (Best Model) - Loss: 0.6532 - Accuracy: 0.6970 - F1: 0.6967
sub_15:Test (Best Model) - Loss: 0.6177 - Accuracy: 0.8750 - F1: 0.8730
sub_21:Test (Best Model) - Loss: 0.6423 - Accuracy: 0.8750 - F1: 0.8667
sub_6:Test (Best Model) - Loss: 0.6782 - Accuracy: 0.4375 - F1: 0.3766
sub_13:Test (Best Model) - Loss: 0.6616 - Accuracy: 0.7188 - F1: 0.7117
sub_26:Test (Best Model) - Loss: 0.5942 - Accuracy: 0.9394 - F1: 0.9393
sub_29:Test (Best Model) - Loss: 0.6637 - Accuracy: 0.6875 - F1: 0.6863
sub_5:Test (Best Model) - Loss: 0.6329 - Accuracy: 0.7812 - F1: 0.7519
sub_19:Test (Best Model) - Loss: 0.6250 - Accuracy: 0.8125 - F1: 0.8118
sub_9:Test (Best Model) - Loss: 0.5601 - Accuracy: 0.9688 - F1: 0.9680
sub_8:Test (Best Model) - Loss: 0.6289 - Accuracy: 0.9062 - F1: 0.9054
sub_7:Test (Best Model) - Loss: 0.6366 - Accuracy: 0.8125 - F1: 0.8000
sub_24:Test (Best Model) - Loss: 0.6571 - Accuracy: 0.7188 - F1: 0.7163
sub_16:Test (Best Model) - Loss: 0.6265 - Accuracy: 0.8438 - F1: 0.8424
sub_22:Test (Best Model) - Loss: 0.6568 - Accuracy: 0.6562 - F1: 0.6476
sub_3:Test (Best Model) - Loss: 0.6679 - Accuracy: 0.6875 - F1: 0.6875
sub_27:Test (Best Model) - Loss: 0.5894 - Accuracy: 0.9394 - F1: 0.9380
sub_10:Test (Best Model) - Loss: 0.6396 - Accuracy: 0.7812 - F1: 0.7810
sub_17:Test (Best Model) - Loss: 0.5894 - Accuracy: 0.9394 - F1: 0.9380
sub_12:Test (Best Model) - Loss: 0.6192 - Accuracy: 0.7812 - F1: 0.7519
sub_13:Test (Best Model) - Loss: 0.6621 - Accuracy: 0.6970 - F1: 0.6827
sub_23:Test (Best Model) - Loss: 0.6412 - Accuracy: 0.6667 - F1: 0.6667
sub_18:Test (Best Model) - Loss: 0.5959 - Accuracy: 1.0000 - F1: 1.0000
sub_21:Test (Best Model) - Loss: 0.6592 - Accuracy: 0.7500 - F1: 0.7409
sub_4:Test (Best Model) - Loss: 0.6225 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.5926 - Accuracy: 0.9688 - F1: 0.9685
sub_29:Test (Best Model) - Loss: 0.6194 - Accuracy: 0.9062 - F1: 0.9015
sub_7:Test (Best Model) - Loss: 0.6398 - Accuracy: 0.8438 - F1: 0.8303
sub_5:Test (Best Model) - Loss: 0.6363 - Accuracy: 0.6875 - F1: 0.6761
sub_2:Test (Best Model) - Loss: 0.6481 - Accuracy: 0.6970 - F1: 0.6898
sub_28:Test (Best Model) - Loss: 0.6002 - Accuracy: 0.9375 - F1: 0.9365
sub_14:Test (Best Model) - Loss: 0.6459 - Accuracy: 0.7812 - F1: 0.7793
sub_11:Test (Best Model) - Loss: 0.6566 - Accuracy: 0.7273 - F1: 0.7263
sub_20:Test (Best Model) - Loss: 0.6230 - Accuracy: 0.8438 - F1: 0.8398
sub_19:Test (Best Model) - Loss: 0.6456 - Accuracy: 0.7188 - F1: 0.6632
sub_16:Test (Best Model) - Loss: 0.6868 - Accuracy: 0.5000 - F1: 0.5000
sub_26:Test (Best Model) - Loss: 0.6298 - Accuracy: 0.8182 - F1: 0.8180
sub_3:Test (Best Model) - Loss: 0.6367 - Accuracy: 0.7879 - F1: 0.7806
sub_27:Test (Best Model) - Loss: 0.6504 - Accuracy: 0.7576 - F1: 0.7462
sub_24:Test (Best Model) - Loss: 0.6526 - Accuracy: 0.7188 - F1: 0.7163
sub_17:Test (Best Model) - Loss: 0.6504 - Accuracy: 0.7576 - F1: 0.7462
sub_9:Test (Best Model) - Loss: 0.6698 - Accuracy: 0.5312 - F1: 0.5195
sub_25:Test (Best Model) - Loss: 0.6438 - Accuracy: 0.7273 - F1: 0.7102
sub_8:Test (Best Model) - Loss: 0.6195 - Accuracy: 0.8125 - F1: 0.8000
sub_23:Test (Best Model) - Loss: 0.6511 - Accuracy: 0.6970 - F1: 0.6726
sub_21:Test (Best Model) - Loss: 0.6572 - Accuracy: 0.6562 - F1: 0.6559
sub_15:Test (Best Model) - Loss: 0.6008 - Accuracy: 0.9375 - F1: 0.9352
sub_10:Test (Best Model) - Loss: 0.6737 - Accuracy: 0.8750 - F1: 0.8667
sub_6:Test (Best Model) - Loss: 0.6200 - Accuracy: 0.8125 - F1: 0.8000
sub_22:Test (Best Model) - Loss: 0.6109 - Accuracy: 0.9394 - F1: 0.9393
sub_2:Test (Best Model) - Loss: 0.6231 - Accuracy: 0.9062 - F1: 0.9054
sub_19:Test (Best Model) - Loss: 0.6294 - Accuracy: 0.6875 - F1: 0.6364
sub_29:Test (Best Model) - Loss: 0.6431 - Accuracy: 0.8438 - F1: 0.8398
sub_20:Test (Best Model) - Loss: 0.6695 - Accuracy: 0.7500 - F1: 0.7500
sub_17:Test (Best Model) - Loss: 0.6335 - Accuracy: 0.9394 - F1: 0.9393
sub_16:Test (Best Model) - Loss: 0.6984 - Accuracy: 0.5625 - F1: 0.5556
sub_12:Test (Best Model) - Loss: 0.6504 - Accuracy: 0.7576 - F1: 0.7273
sub_27:Test (Best Model) - Loss: 0.6335 - Accuracy: 0.9394 - F1: 0.9393
sub_24:Test (Best Model) - Loss: 0.6557 - Accuracy: 0.8125 - F1: 0.8118
sub_5:Test (Best Model) - Loss: 0.6484 - Accuracy: 0.7188 - F1: 0.7117
sub_4:Test (Best Model) - Loss: 0.6621 - Accuracy: 0.6061 - F1: 0.5815
sub_13:Test (Best Model) - Loss: 0.6297 - Accuracy: 0.9091 - F1: 0.9060
sub_1:Test (Best Model) - Loss: 0.6275 - Accuracy: 0.8788 - F1: 0.8759
sub_23:Test (Best Model) - Loss: 0.6943 - Accuracy: 0.5000 - F1: 0.4921
sub_25:Test (Best Model) - Loss: 0.6596 - Accuracy: 0.7188 - F1: 0.7185
sub_18:Test (Best Model) - Loss: 0.6445 - Accuracy: 0.7273 - F1: 0.6997
sub_14:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.5938 - F1: 0.5934
sub_7:Test (Best Model) - Loss: 0.6075 - Accuracy: 0.9375 - F1: 0.9365
sub_9:Test (Best Model) - Loss: 0.6169 - Accuracy: 0.8750 - F1: 0.8704
sub_28:Test (Best Model) - Loss: 0.6461 - Accuracy: 0.8125 - F1: 0.8095
sub_15:Test (Best Model) - Loss: 0.6315 - Accuracy: 0.8438 - F1: 0.8436
sub_8:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.6250 - F1: 0.6235
sub_3:Test (Best Model) - Loss: 0.6210 - Accuracy: 0.9091 - F1: 0.9077
sub_11:Test (Best Model) - Loss: 0.6067 - Accuracy: 0.8182 - F1: 0.8167
sub_26:Test (Best Model) - Loss: 0.6605 - Accuracy: 0.5938 - F1: 0.5589
sub_21:Test (Best Model) - Loss: 0.6201 - Accuracy: 0.8125 - F1: 0.8095
sub_10:Test (Best Model) - Loss: 0.6982 - Accuracy: 0.4375 - F1: 0.3043
sub_24:Test (Best Model) - Loss: 0.6678 - Accuracy: 0.7500 - F1: 0.7460
sub_7:Test (Best Model) - Loss: 0.6705 - Accuracy: 0.7812 - F1: 0.7703
sub_27:Test (Best Model) - Loss: 0.6460 - Accuracy: 0.7576 - F1: 0.7556
sub_6:Test (Best Model) - Loss: 0.6292 - Accuracy: 0.8182 - F1: 0.8180
sub_16:Test (Best Model) - Loss: 0.6697 - Accuracy: 0.6562 - F1: 0.6102
sub_17:Test (Best Model) - Loss: 0.6460 - Accuracy: 0.7576 - F1: 0.7556
sub_20:Test (Best Model) - Loss: 0.6348 - Accuracy: 0.7812 - F1: 0.7793
sub_2:Test (Best Model) - Loss: 0.6503 - Accuracy: 0.8750 - F1: 0.8745
sub_23:Test (Best Model) - Loss: 0.6728 - Accuracy: 0.6875 - F1: 0.6825
sub_28:Test (Best Model) - Loss: 0.6206 - Accuracy: 0.8438 - F1: 0.8359
sub_22:Test (Best Model) - Loss: 0.6612 - Accuracy: 0.6667 - F1: 0.6654
sub_8:Test (Best Model) - Loss: 0.6453 - Accuracy: 0.8125 - F1: 0.8057
sub_29:Test (Best Model) - Loss: 0.6178 - Accuracy: 0.9688 - F1: 0.9685
sub_21:Test (Best Model) - Loss: 0.6540 - Accuracy: 0.7500 - F1: 0.7500
sub_5:Test (Best Model) - Loss: 0.6162 - Accuracy: 1.0000 - F1: 1.0000
sub_14:Test (Best Model) - Loss: 0.6370 - Accuracy: 0.7812 - F1: 0.7758
sub_12:Test (Best Model) - Loss: 0.6369 - Accuracy: 0.7879 - F1: 0.7806
sub_4:Test (Best Model) - Loss: 0.6305 - Accuracy: 0.8182 - F1: 0.8167
sub_15:Test (Best Model) - Loss: 0.6224 - Accuracy: 0.9062 - F1: 0.9062
sub_19:Test (Best Model) - Loss: 0.5883 - Accuracy: 0.9062 - F1: 0.9039
sub_9:Test (Best Model) - Loss: 0.6279 - Accuracy: 0.8438 - F1: 0.8424
sub_13:Test (Best Model) - Loss: 0.6515 - Accuracy: 0.7879 - F1: 0.7664
sub_18:Test (Best Model) - Loss: 0.6233 - Accuracy: 0.8750 - F1: 0.8750
sub_10:Test (Best Model) - Loss: 0.6881 - Accuracy: 0.5312 - F1: 0.5195
sub_25:Test (Best Model) - Loss: 0.6178 - Accuracy: 0.9062 - F1: 0.9054
sub_23:Test (Best Model) - Loss: 0.6377 - Accuracy: 0.8750 - F1: 0.8730
sub_26:Test (Best Model) - Loss: 0.6248 - Accuracy: 0.8750 - F1: 0.8750
sub_11:Test (Best Model) - Loss: 0.6083 - Accuracy: 0.9394 - F1: 0.9389
sub_3:Test (Best Model) - Loss: 0.6293 - Accuracy: 0.6970 - F1: 0.6827
sub_1:Test (Best Model) - Loss: 0.6405 - Accuracy: 0.8485 - F1: 0.8485
sub_7:Test (Best Model) - Loss: 0.6303 - Accuracy: 0.8750 - F1: 0.8745
sub_21:Test (Best Model) - Loss: 0.6519 - Accuracy: 0.7188 - F1: 0.6946
sub_22:Test (Best Model) - Loss: 0.6669 - Accuracy: 0.5455 - F1: 0.5438
sub_6:Test (Best Model) - Loss: 0.6469 - Accuracy: 0.7879 - F1: 0.7746
sub_12:Test (Best Model) - Loss: 0.6175 - Accuracy: 0.8182 - F1: 0.8036
sub_5:Test (Best Model) - Loss: 0.6055 - Accuracy: 1.0000 - F1: 1.0000
sub_20:Test (Best Model) - Loss: 0.6608 - Accuracy: 0.7188 - F1: 0.7046
sub_16:Test (Best Model) - Loss: 0.6948 - Accuracy: 0.4062 - F1: 0.3267
sub_29:Test (Best Model) - Loss: 0.6308 - Accuracy: 0.8438 - F1: 0.8436
sub_19:Test (Best Model) - Loss: 0.6239 - Accuracy: 0.9375 - F1: 0.9365
sub_17:Test (Best Model) - Loss: 0.6510 - Accuracy: 0.7879 - F1: 0.7847
sub_2:Test (Best Model) - Loss: 0.6772 - Accuracy: 0.6562 - F1: 0.6532
sub_13:Test (Best Model) - Loss: 0.6515 - Accuracy: 0.6061 - F1: 0.5662
sub_27:Test (Best Model) - Loss: 0.6510 - Accuracy: 0.7879 - F1: 0.7847
sub_15:Test (Best Model) - Loss: 0.6145 - Accuracy: 0.8750 - F1: 0.8750
sub_24:Test (Best Model) - Loss: 0.6130 - Accuracy: 0.8438 - F1: 0.8424
sub_25:Test (Best Model) - Loss: 0.6872 - Accuracy: 0.5938 - F1: 0.5901
sub_14:Test (Best Model) - Loss: 0.6727 - Accuracy: 0.6250 - F1: 0.6190
sub_8:Test (Best Model) - Loss: 0.6699 - Accuracy: 0.7500 - F1: 0.7460
sub_26:Test (Best Model) - Loss: 0.6931 - Accuracy: 0.4688 - F1: 0.4231
sub_9:Test (Best Model) - Loss: 0.6507 - Accuracy: 0.6875 - F1: 0.6863
sub_3:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5758 - F1: 0.5754
sub_28:Test (Best Model) - Loss: 0.6472 - Accuracy: 0.8750 - F1: 0.8667
sub_4:Test (Best Model) - Loss: 0.6234 - Accuracy: 0.8788 - F1: 0.8787
sub_22:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.5758 - F1: 0.5417
sub_17:Test (Best Model) - Loss: 0.6662 - Accuracy: 0.6364 - F1: 0.6333
sub_2:Test (Best Model) - Loss: 0.6356 - Accuracy: 0.9375 - F1: 0.9365
sub_25:Test (Best Model) - Loss: 0.6777 - Accuracy: 0.5938 - F1: 0.5589
sub_29:Test (Best Model) - Loss: 0.5999 - Accuracy: 1.0000 - F1: 1.0000
sub_23:Test (Best Model) - Loss: 0.6560 - Accuracy: 0.6562 - F1: 0.6390
sub_11:Test (Best Model) - Loss: 0.6595 - Accuracy: 0.6364 - F1: 0.6071
sub_10:Test (Best Model) - Loss: 0.6856 - Accuracy: 0.7188 - F1: 0.7046
sub_18:Test (Best Model) - Loss: 0.6610 - Accuracy: 0.6250 - F1: 0.6000
sub_1:Test (Best Model) - Loss: 0.6147 - Accuracy: 0.9091 - F1: 0.9060
sub_27:Test (Best Model) - Loss: 0.6662 - Accuracy: 0.6364 - F1: 0.6333
sub_7:Test (Best Model) - Loss: 0.6475 - Accuracy: 0.9062 - F1: 0.9039
sub_6:Test (Best Model) - Loss: 0.6360 - Accuracy: 0.8788 - F1: 0.8778
sub_15:Test (Best Model) - Loss: 0.6279 - Accuracy: 0.8750 - F1: 0.8750
sub_21:Test (Best Model) - Loss: 0.6287 - Accuracy: 0.9375 - F1: 0.9365
sub_5:Test (Best Model) - Loss: 0.6092 - Accuracy: 0.8750 - F1: 0.8750
sub_8:Test (Best Model) - Loss: 0.6603 - Accuracy: 0.7188 - F1: 0.6811
sub_20:Test (Best Model) - Loss: 0.6451 - Accuracy: 0.7812 - F1: 0.7703
sub_16:Test (Best Model) - Loss: 0.6556 - Accuracy: 0.8125 - F1: 0.7922
sub_9:Test (Best Model) - Loss: 0.6174 - Accuracy: 0.8750 - F1: 0.8667
sub_19:Test (Best Model) - Loss: 0.6323 - Accuracy: 0.7812 - F1: 0.7519
sub_26:Test (Best Model) - Loss: 0.6646 - Accuracy: 0.6250 - F1: 0.6113
sub_25:Test (Best Model) - Loss: 0.6054 - Accuracy: 0.9688 - F1: 0.9680
sub_4:Test (Best Model) - Loss: 0.6357 - Accuracy: 0.8182 - F1: 0.8180
sub_14:Test (Best Model) - Loss: 0.6817 - Accuracy: 0.5625 - F1: 0.5466
sub_10:Test (Best Model) - Loss: 0.6910 - Accuracy: 0.4375 - F1: 0.3766
sub_3:Test (Best Model) - Loss: 0.6373 - Accuracy: 0.7879 - F1: 0.7847
sub_1:Test (Best Model) - Loss: 0.6511 - Accuracy: 0.6364 - F1: 0.6071
sub_22:Test (Best Model) - Loss: 0.6882 - Accuracy: 0.5758 - F1: 0.5417
sub_13:Test (Best Model) - Loss: 0.6148 - Accuracy: 0.8788 - F1: 0.8778
sub_24:Test (Best Model) - Loss: 0.6354 - Accuracy: 0.8750 - F1: 0.8745
sub_15:Test (Best Model) - Loss: 0.6052 - Accuracy: 0.9062 - F1: 0.9062
sub_11:Test (Best Model) - Loss: 0.6482 - Accuracy: 0.7273 - F1: 0.7263
sub_9:Test (Best Model) - Loss: 0.6362 - Accuracy: 0.8125 - F1: 0.7922
sub_29:Test (Best Model) - Loss: 0.6528 - Accuracy: 0.8485 - F1: 0.8479
sub_28:Test (Best Model) - Loss: 0.6642 - Accuracy: 0.7812 - F1: 0.7625
sub_2:Test (Best Model) - Loss: 0.6258 - Accuracy: 0.8750 - F1: 0.8730
sub_23:Test (Best Model) - Loss: 0.5883 - Accuracy: 1.0000 - F1: 1.0000
sub_5:Test (Best Model) - Loss: 0.6332 - Accuracy: 0.9688 - F1: 0.9685
sub_17:Test (Best Model) - Loss: 0.6245 - Accuracy: 0.8788 - F1: 0.8787
sub_7:Test (Best Model) - Loss: 0.6753 - Accuracy: 0.5625 - F1: 0.5608
sub_20:Test (Best Model) - Loss: 0.6764 - Accuracy: 0.5000 - F1: 0.4921
sub_4:Test (Best Model) - Loss: 0.6113 - Accuracy: 0.9697 - F1: 0.9696
sub_12:Test (Best Model) - Loss: 0.6362 - Accuracy: 0.8485 - F1: 0.8433
sub_21:Test (Best Model) - Loss: 0.6967 - Accuracy: 0.4062 - F1: 0.2889
sub_19:Test (Best Model) - Loss: 0.6005 - Accuracy: 0.9375 - F1: 0.9352
sub_18:Test (Best Model) - Loss: 0.6218 - Accuracy: 0.9688 - F1: 0.9685
sub_27:Test (Best Model) - Loss: 0.6245 - Accuracy: 0.8788 - F1: 0.8787
sub_14:Test (Best Model) - Loss: 0.6474 - Accuracy: 0.8750 - F1: 0.8667
sub_8:Test (Best Model) - Loss: 0.6682 - Accuracy: 0.6250 - F1: 0.6190
sub_6:Test (Best Model) - Loss: 0.6326 - Accuracy: 0.8788 - F1: 0.8731
sub_1:Test (Best Model) - Loss: 0.5986 - Accuracy: 0.9394 - F1: 0.9393
sub_3:Test (Best Model) - Loss: 0.6465 - Accuracy: 1.0000 - F1: 1.0000
sub_29:Test (Best Model) - Loss: 0.6109 - Accuracy: 0.8485 - F1: 0.8390
sub_26:Test (Best Model) - Loss: 0.6205 - Accuracy: 0.8750 - F1: 0.8730
sub_25:Test (Best Model) - Loss: 0.6755 - Accuracy: 0.5938 - F1: 0.5901
sub_13:Test (Best Model) - Loss: 0.7240 - Accuracy: 0.3438 - F1: 0.2874
sub_22:Test (Best Model) - Loss: 0.7060 - Accuracy: 0.4688 - F1: 0.4682
sub_28:Test (Best Model) - Loss: 0.6530 - Accuracy: 0.9062 - F1: 0.9062
sub_16:Test (Best Model) - Loss: 0.5958 - Accuracy: 0.8750 - F1: 0.8667
sub_9:Test (Best Model) - Loss: 0.6783 - Accuracy: 0.5625 - F1: 0.5333
sub_12:Test (Best Model) - Loss: 0.6360 - Accuracy: 0.6970 - F1: 0.6827
sub_11:Test (Best Model) - Loss: 0.6212 - Accuracy: 0.8788 - F1: 0.8787
sub_24:Test (Best Model) - Loss: 0.6357 - Accuracy: 0.8125 - F1: 0.8095
sub_5:Test (Best Model) - Loss: 0.6339 - Accuracy: 0.9062 - F1: 0.9062
sub_17:Test (Best Model) - Loss: 0.6426 - Accuracy: 0.7812 - F1: 0.7519
sub_18:Test (Best Model) - Loss: 0.6257 - Accuracy: 0.8438 - F1: 0.8436
sub_25:Test (Best Model) - Loss: 0.6511 - Accuracy: 0.8125 - F1: 0.8095
sub_15:Test (Best Model) - Loss: 0.6340 - Accuracy: 0.9375 - F1: 0.9373
sub_7:Test (Best Model) - Loss: 0.6180 - Accuracy: 0.8438 - F1: 0.8424
sub_13:Test (Best Model) - Loss: 0.6310 - Accuracy: 0.8750 - F1: 0.8704
sub_23:Test (Best Model) - Loss: 0.6780 - Accuracy: 0.6364 - F1: 0.6333
sub_21:Test (Best Model) - Loss: 0.6532 - Accuracy: 0.5938 - F1: 0.5589
sub_2:Test (Best Model) - Loss: 0.6566 - Accuracy: 0.8485 - F1: 0.8462
sub_10:Test (Best Model) - Loss: 0.6370 - Accuracy: 0.7576 - F1: 0.7273
sub_27:Test (Best Model) - Loss: 0.6426 - Accuracy: 0.7812 - F1: 0.7519
sub_9:Test (Best Model) - Loss: 0.6253 - Accuracy: 0.9062 - F1: 0.9039
sub_28:Test (Best Model) - Loss: 0.6494 - Accuracy: 0.8125 - F1: 0.7922
sub_8:Test (Best Model) - Loss: 0.6379 - Accuracy: 0.8125 - F1: 0.7922
sub_4:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.5758 - F1: 0.5417
sub_11:Test (Best Model) - Loss: 0.6671 - Accuracy: 0.7879 - F1: 0.7879
sub_19:Test (Best Model) - Loss: 0.6762 - Accuracy: 0.5938 - F1: 0.5589
sub_3:Test (Best Model) - Loss: 0.6407 - Accuracy: 0.8485 - F1: 0.8462
sub_22:Test (Best Model) - Loss: 0.6188 - Accuracy: 0.9688 - F1: 0.9685
sub_21:Test (Best Model) - Loss: 0.6870 - Accuracy: 0.5312 - F1: 0.4910
sub_14:Test (Best Model) - Loss: 0.6621 - Accuracy: 0.6875 - F1: 0.6825
sub_1:Test (Best Model) - Loss: 0.6503 - Accuracy: 0.8750 - F1: 0.8730
sub_15:Test (Best Model) - Loss: 0.6210 - Accuracy: 0.9375 - F1: 0.9365
sub_29:Test (Best Model) - Loss: 0.5973 - Accuracy: 0.7576 - F1: 0.7273
sub_2:Test (Best Model) - Loss: 0.6823 - Accuracy: 0.4242 - F1: 0.3883
sub_5:Test (Best Model) - Loss: 0.5980 - Accuracy: 0.9688 - F1: 0.9680
sub_26:Test (Best Model) - Loss: 0.6377 - Accuracy: 0.9062 - F1: 0.9015
sub_16:Test (Best Model) - Loss: 0.6545 - Accuracy: 0.8125 - F1: 0.8000
sub_20:Test (Best Model) - Loss: 0.6397 - Accuracy: 0.7576 - F1: 0.7519
sub_6:Test (Best Model) - Loss: 0.6009 - Accuracy: 0.9091 - F1: 0.9060
sub_17:Test (Best Model) - Loss: 0.6376 - Accuracy: 0.8438 - F1: 0.8436
sub_23:Test (Best Model) - Loss: 0.6435 - Accuracy: 0.7879 - F1: 0.7806
sub_18:Test (Best Model) - Loss: 0.5835 - Accuracy: 1.0000 - F1: 1.0000
sub_1:Test (Best Model) - Loss: 0.5930 - Accuracy: 1.0000 - F1: 1.0000
sub_24:Test (Best Model) - Loss: 0.6601 - Accuracy: 0.7812 - F1: 0.7810
sub_7:Test (Best Model) - Loss: 0.6433 - Accuracy: 0.7188 - F1: 0.7185
sub_29:Test (Best Model) - Loss: 0.6853 - Accuracy: 0.6061 - F1: 0.5926
sub_13:Test (Best Model) - Loss: 0.6317 - Accuracy: 0.8438 - F1: 0.8424
sub_16:Test (Best Model) - Loss: 0.6446 - Accuracy: 0.7812 - F1: 0.7703
sub_19:Test (Best Model) - Loss: 0.6538 - Accuracy: 0.6875 - F1: 0.6863
sub_26:Test (Best Model) - Loss: 0.6213 - Accuracy: 0.9375 - F1: 0.9365
sub_21:Test (Best Model) - Loss: 0.6472 - Accuracy: 0.7812 - F1: 0.7810
sub_25:Test (Best Model) - Loss: 0.5990 - Accuracy: 0.9375 - F1: 0.9352
sub_15:Test (Best Model) - Loss: 0.5959 - Accuracy: 0.9062 - F1: 0.9054
sub_10:Test (Best Model) - Loss: 0.6515 - Accuracy: 0.7576 - F1: 0.7574
sub_12:Test (Best Model) - Loss: 0.7252 - Accuracy: 0.4062 - F1: 0.2889
sub_11:Test (Best Model) - Loss: 0.6013 - Accuracy: 0.9091 - F1: 0.9088
sub_9:Test (Best Model) - Loss: 0.5894 - Accuracy: 0.9375 - F1: 0.9365
sub_20:Test (Best Model) - Loss: 0.6324 - Accuracy: 0.9091 - F1: 0.9060
sub_14:Test (Best Model) - Loss: 0.7015 - Accuracy: 0.4688 - F1: 0.4555
sub_8:Test (Best Model) - Loss: 0.6064 - Accuracy: 0.9688 - F1: 0.9680
sub_27:Test (Best Model) - Loss: 0.6376 - Accuracy: 0.8438 - F1: 0.8436
sub_5:Test (Best Model) - Loss: 0.6285 - Accuracy: 0.9688 - F1: 0.9680
sub_7:Test (Best Model) - Loss: 0.6794 - Accuracy: 0.5938 - F1: 0.5934
sub_28:Test (Best Model) - Loss: 0.6879 - Accuracy: 0.5000 - F1: 0.4980
sub_2:Test (Best Model) - Loss: 0.6547 - Accuracy: 0.7273 - F1: 0.7263
sub_4:Test (Best Model) - Loss: 0.6368 - Accuracy: 0.8485 - F1: 0.8479
sub_6:Test (Best Model) - Loss: 0.6828 - Accuracy: 0.5758 - F1: 0.5722
sub_3:Test (Best Model) - Loss: 0.6486 - Accuracy: 0.7273 - F1: 0.7232
sub_9:Test (Best Model) - Loss: 0.6476 - Accuracy: 0.6562 - F1: 0.5594
sub_13:Test (Best Model) - Loss: 0.6565 - Accuracy: 0.7500 - F1: 0.7091
sub_26:Test (Best Model) - Loss: 0.6435 - Accuracy: 0.7188 - F1: 0.6946
sub_16:Test (Best Model) - Loss: 0.6970 - Accuracy: 0.4375 - F1: 0.4286
sub_11:Test (Best Model) - Loss: 0.6655 - Accuracy: 0.7576 - F1: 0.7574
sub_24:Test (Best Model) - Loss: 0.6488 - Accuracy: 0.8438 - F1: 0.8398
sub_14:Test (Best Model) - Loss: 0.6020 - Accuracy: 0.9062 - F1: 0.9015
sub_22:Test (Best Model) - Loss: 0.7022 - Accuracy: 0.4688 - F1: 0.4555
sub_12:Test (Best Model) - Loss: 0.6380 - Accuracy: 0.8750 - F1: 0.8730
sub_15:Test (Best Model) - Loss: 0.7074 - Accuracy: 0.3125 - F1: 0.3098
sub_28:Test (Best Model) - Loss: 0.6512 - Accuracy: 0.7812 - F1: 0.7793
sub_19:Test (Best Model) - Loss: 0.6459 - Accuracy: 0.7812 - F1: 0.7793
sub_18:Test (Best Model) - Loss: 0.6244 - Accuracy: 0.9375 - F1: 0.9352
sub_17:Test (Best Model) - Loss: 0.5991 - Accuracy: 0.9062 - F1: 0.9039
sub_26:Test (Best Model) - Loss: 0.6498 - Accuracy: 0.7500 - F1: 0.7409
sub_9:Test (Best Model) - Loss: 0.6458 - Accuracy: 0.7812 - F1: 0.7793
sub_1:Test (Best Model) - Loss: 0.5544 - Accuracy: 0.9375 - F1: 0.9352
sub_8:Test (Best Model) - Loss: 0.5939 - Accuracy: 0.9375 - F1: 0.9352
sub_7:Test (Best Model) - Loss: 0.6581 - Accuracy: 0.7812 - F1: 0.7810
sub_2:Test (Best Model) - Loss: 0.6516 - Accuracy: 0.6667 - F1: 0.5935
sub_27:Test (Best Model) - Loss: 0.5991 - Accuracy: 0.9062 - F1: 0.9039
sub_29:Test (Best Model) - Loss: 0.6704 - Accuracy: 0.6970 - F1: 0.6944
sub_20:Test (Best Model) - Loss: 0.6706 - Accuracy: 0.6061 - F1: 0.5926
sub_21:Test (Best Model) - Loss: 0.6791 - Accuracy: 0.5625 - F1: 0.5625
sub_10:Test (Best Model) - Loss: 0.6064 - Accuracy: 0.9091 - F1: 0.9060
sub_6:Test (Best Model) - Loss: 0.6252 - Accuracy: 0.9091 - F1: 0.9077
sub_13:Test (Best Model) - Loss: 0.6724 - Accuracy: 0.5312 - F1: 0.5195
sub_14:Test (Best Model) - Loss: 0.6425 - Accuracy: 0.9062 - F1: 0.9039
sub_15:Test (Best Model) - Loss: 0.6196 - Accuracy: 0.9375 - F1: 0.9365
sub_23:Test (Best Model) - Loss: 0.6396 - Accuracy: 0.7879 - F1: 0.7806
sub_3:Test (Best Model) - Loss: 0.6515 - Accuracy: 0.7576 - F1: 0.7381
sub_24:Test (Best Model) - Loss: 0.6321 - Accuracy: 0.9062 - F1: 0.9039
sub_22:Test (Best Model) - Loss: 0.6830 - Accuracy: 0.5938 - F1: 0.5934
sub_5:Test (Best Model) - Loss: 0.5688 - Accuracy: 1.0000 - F1: 1.0000
sub_16:Test (Best Model) - Loss: 0.7129 - Accuracy: 0.3750 - F1: 0.3333
sub_25:Test (Best Model) - Loss: 0.5962 - Accuracy: 0.9375 - F1: 0.9352
sub_1:Test (Best Model) - Loss: 0.6370 - Accuracy: 0.8750 - F1: 0.8745
sub_11:Test (Best Model) - Loss: 0.6795 - Accuracy: 0.6061 - F1: 0.5926
sub_17:Test (Best Model) - Loss: 0.7155 - Accuracy: 0.3438 - F1: 0.3431
sub_18:Test (Best Model) - Loss: 0.6013 - Accuracy: 0.9688 - F1: 0.9685
sub_27:Test (Best Model) - Loss: 0.7155 - Accuracy: 0.3438 - F1: 0.3431
sub_4:Test (Best Model) - Loss: 0.6296 - Accuracy: 0.7879 - F1: 0.7806
sub_19:Test (Best Model) - Loss: 0.6917 - Accuracy: 0.4688 - F1: 0.3191
sub_28:Test (Best Model) - Loss: 0.6681 - Accuracy: 0.5938 - F1: 0.5901
sub_26:Test (Best Model) - Loss: 0.6441 - Accuracy: 0.7500 - F1: 0.7091
sub_12:Test (Best Model) - Loss: 0.6388 - Accuracy: 0.7812 - F1: 0.7703
sub_20:Test (Best Model) - Loss: 0.6867 - Accuracy: 0.5455 - F1: 0.5438
sub_23:Test (Best Model) - Loss: 0.6934 - Accuracy: 0.5758 - F1: 0.5754
sub_2:Test (Best Model) - Loss: 0.6693 - Accuracy: 0.6970 - F1: 0.6944
sub_18:Test (Best Model) - Loss: 0.6306 - Accuracy: 0.7812 - F1: 0.7519
sub_3:Test (Best Model) - Loss: 0.6656 - Accuracy: 0.7576 - F1: 0.7574
sub_8:Test (Best Model) - Loss: 0.6206 - Accuracy: 0.8750 - F1: 0.8704
sub_10:Test (Best Model) - Loss: 0.6430 - Accuracy: 0.8485 - F1: 0.8479
sub_6:Test (Best Model) - Loss: 0.5616 - Accuracy: 0.9697 - F1: 0.9692
sub_11:Test (Best Model) - Loss: 0.7018 - Accuracy: 0.4545 - F1: 0.4417
sub_20:Test (Best Model) - Loss: 0.6387 - Accuracy: 0.7879 - F1: 0.7871
sub_1:Test (Best Model) - Loss: 0.6785 - Accuracy: 0.5000 - F1: 0.4459
sub_27:Test (Best Model) - Loss: 0.6238 - Accuracy: 0.9688 - F1: 0.9680
sub_19:Test (Best Model) - Loss: 0.6225 - Accuracy: 0.8125 - F1: 0.8118
sub_17:Test (Best Model) - Loss: 0.6238 - Accuracy: 0.9688 - F1: 0.9680
sub_25:Test (Best Model) - Loss: 0.6407 - Accuracy: 0.6250 - F1: 0.6113
sub_16:Test (Best Model) - Loss: 0.6359 - Accuracy: 0.6875 - F1: 0.6537
sub_14:Test (Best Model) - Loss: 0.6134 - Accuracy: 0.9375 - F1: 0.9373
sub_22:Test (Best Model) - Loss: 0.6031 - Accuracy: 0.9375 - F1: 0.9352
sub_4:Test (Best Model) - Loss: 0.6793 - Accuracy: 0.6364 - F1: 0.6071
sub_28:Test (Best Model) - Loss: 0.6505 - Accuracy: 1.0000 - F1: 1.0000
sub_23:Test (Best Model) - Loss: 0.6855 - Accuracy: 0.5455 - F1: 0.5171
sub_10:Test (Best Model) - Loss: 0.6523 - Accuracy: 0.6970 - F1: 0.6898
sub_12:Test (Best Model) - Loss: 0.6498 - Accuracy: 0.9062 - F1: 0.9039
sub_8:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5000 - F1: 0.4980
sub_18:Test (Best Model) - Loss: 0.6322 - Accuracy: 0.9062 - F1: 0.9062
sub_14:Test (Best Model) - Loss: 0.6556 - Accuracy: 0.6250 - F1: 0.5362
sub_4:Test (Best Model) - Loss: 0.6818 - Accuracy: 0.5455 - F1: 0.5387
sub_6:Test (Best Model) - Loss: 0.6428 - Accuracy: 0.8788 - F1: 0.8778
sub_18:Test (Best Model) - Loss: 0.6623 - Accuracy: 0.7812 - F1: 0.7703
sub_28:Test (Best Model) - Loss: 0.6799 - Accuracy: 0.5312 - F1: 0.4910
sub_12:Test (Best Model) - Loss: 0.6169 - Accuracy: 0.9375 - F1: 0.9365
sub_6:Test (Best Model) - Loss: 0.7140 - Accuracy: 0.3939 - F1: 0.3452

=== Summary Results ===

acc: 76.41 ± 5.43
F1: 75.28 ± 5.73
acc-in: 79.80 ± 4.62
F1-in: 78.86 ± 4.84
