lr: 1e-05
sub_14:Test (Best Model) - Loss: 0.6589 - Accuracy: 0.6429 - F1: 0.6050
sub_6:Test (Best Model) - Loss: 0.6455 - Accuracy: 0.6905 - F1: 0.6630
sub_8:Test (Best Model) - Loss: 0.5610 - Accuracy: 0.9405 - F1: 0.9405
sub_7:Test (Best Model) - Loss: 0.6737 - Accuracy: 0.5833 - F1: 0.5804
sub_5:Test (Best Model) - Loss: 0.6901 - Accuracy: 0.5833 - F1: 0.5785
sub_1:Test (Best Model) - Loss: 0.6174 - Accuracy: 0.7381 - F1: 0.7224
sub_10:Test (Best Model) - Loss: 0.6435 - Accuracy: 0.6310 - F1: 0.5728
sub_2:Test (Best Model) - Loss: 0.6031 - Accuracy: 0.8452 - F1: 0.8425
sub_9:Test (Best Model) - Loss: 0.5522 - Accuracy: 0.9881 - F1: 0.9881
sub_12:Test (Best Model) - Loss: 0.6021 - Accuracy: 0.8452 - F1: 0.8414
sub_11:Test (Best Model) - Loss: 0.5926 - Accuracy: 0.8333 - F1: 0.8286
sub_3:Test (Best Model) - Loss: 0.6303 - Accuracy: 0.8333 - F1: 0.8333
sub_4:Test (Best Model) - Loss: 0.6101 - Accuracy: 0.8452 - F1: 0.8452
sub_13:Test (Best Model) - Loss: 0.6806 - Accuracy: 0.5476 - F1: 0.4708
sub_10:Test (Best Model) - Loss: 0.6650 - Accuracy: 0.6667 - F1: 0.6421
sub_14:Test (Best Model) - Loss: 0.6451 - Accuracy: 0.7500 - F1: 0.7491
sub_8:Test (Best Model) - Loss: 0.5897 - Accuracy: 0.9167 - F1: 0.9166
sub_3:Test (Best Model) - Loss: 0.6455 - Accuracy: 0.7738 - F1: 0.7712
sub_7:Test (Best Model) - Loss: 0.6812 - Accuracy: 0.6310 - F1: 0.6309
sub_6:Test (Best Model) - Loss: 0.6439 - Accuracy: 0.8095 - F1: 0.8091
sub_9:Test (Best Model) - Loss: 0.6394 - Accuracy: 0.8214 - F1: 0.8170
sub_12:Test (Best Model) - Loss: 0.6464 - Accuracy: 0.6905 - F1: 0.6677
sub_5:Test (Best Model) - Loss: 0.6819 - Accuracy: 0.5238 - F1: 0.5170
sub_11:Test (Best Model) - Loss: 0.6138 - Accuracy: 0.8452 - F1: 0.8425
sub_1:Test (Best Model) - Loss: 0.6377 - Accuracy: 0.6905 - F1: 0.6677
sub_13:Test (Best Model) - Loss: 0.6694 - Accuracy: 0.5833 - F1: 0.5176
sub_2:Test (Best Model) - Loss: 0.5997 - Accuracy: 0.7262 - F1: 0.7079
sub_12:Test (Best Model) - Loss: 0.6237 - Accuracy: 0.8333 - F1: 0.8333
sub_4:Test (Best Model) - Loss: 0.6424 - Accuracy: 0.7857 - F1: 0.7852
sub_10:Test (Best Model) - Loss: 0.6086 - Accuracy: 0.7500 - F1: 0.7418
sub_5:Test (Best Model) - Loss: 0.6539 - Accuracy: 0.6905 - F1: 0.6719
sub_14:Test (Best Model) - Loss: 0.6102 - Accuracy: 0.7976 - F1: 0.7910
sub_6:Test (Best Model) - Loss: 0.6715 - Accuracy: 0.6548 - F1: 0.6317
sub_8:Test (Best Model) - Loss: 0.5249 - Accuracy: 0.9405 - F1: 0.9404
sub_3:Test (Best Model) - Loss: 0.6545 - Accuracy: 0.6310 - F1: 0.5951
sub_1:Test (Best Model) - Loss: 0.6534 - Accuracy: 0.7024 - F1: 0.6926
sub_7:Test (Best Model) - Loss: 0.6555 - Accuracy: 0.6429 - F1: 0.6327
sub_2:Test (Best Model) - Loss: 0.5753 - Accuracy: 0.7857 - F1: 0.7796
sub_9:Test (Best Model) - Loss: 0.5902 - Accuracy: 0.9286 - F1: 0.9282
sub_3:Test (Best Model) - Loss: 0.6320 - Accuracy: 0.8214 - F1: 0.8208
sub_13:Test (Best Model) - Loss: 0.6292 - Accuracy: 0.7976 - F1: 0.7962
sub_10:Test (Best Model) - Loss: 0.6139 - Accuracy: 0.7619 - F1: 0.7504
sub_4:Test (Best Model) - Loss: 0.5977 - Accuracy: 0.8333 - F1: 0.8286
sub_11:Test (Best Model) - Loss: 0.5706 - Accuracy: 0.8810 - F1: 0.8799
sub_5:Test (Best Model) - Loss: 0.6558 - Accuracy: 0.7024 - F1: 0.7020
sub_14:Test (Best Model) - Loss: 0.6448 - Accuracy: 0.7262 - F1: 0.7172
sub_12:Test (Best Model) - Loss: 0.6030 - Accuracy: 0.8333 - F1: 0.8299
sub_2:Test (Best Model) - Loss: 0.6318 - Accuracy: 0.6786 - F1: 0.6525
sub_6:Test (Best Model) - Loss: 0.6639 - Accuracy: 0.6190 - F1: 0.6007
sub_13:Test (Best Model) - Loss: 0.6696 - Accuracy: 0.6429 - F1: 0.6294
sub_7:Test (Best Model) - Loss: 0.6693 - Accuracy: 0.6190 - F1: 0.6082
sub_4:Test (Best Model) - Loss: 0.6301 - Accuracy: 0.7738 - F1: 0.7683
sub_1:Test (Best Model) - Loss: 0.6247 - Accuracy: 0.7976 - F1: 0.7969
sub_8:Test (Best Model) - Loss: 0.5556 - Accuracy: 0.9048 - F1: 0.9043
sub_3:Test (Best Model) - Loss: 0.6334 - Accuracy: 0.6905 - F1: 0.6677
sub_9:Test (Best Model) - Loss: 0.5893 - Accuracy: 0.7857 - F1: 0.7776
sub_11:Test (Best Model) - Loss: 0.6045 - Accuracy: 0.8214 - F1: 0.8194
sub_12:Test (Best Model) - Loss: 0.6152 - Accuracy: 0.8571 - F1: 0.8558
sub_10:Test (Best Model) - Loss: 0.6350 - Accuracy: 0.6667 - F1: 0.6370
sub_2:Test (Best Model) - Loss: 0.6081 - Accuracy: 0.7500 - F1: 0.7365
sub_6:Test (Best Model) - Loss: 0.6346 - Accuracy: 0.7381 - F1: 0.7255
sub_14:Test (Best Model) - Loss: 0.6420 - Accuracy: 0.6905 - F1: 0.6577
sub_13:Test (Best Model) - Loss: 0.6240 - Accuracy: 0.7976 - F1: 0.7927
sub_5:Test (Best Model) - Loss: 0.6616 - Accuracy: 0.6310 - F1: 0.6219
sub_1:Test (Best Model) - Loss: 0.6419 - Accuracy: 0.7024 - F1: 0.6951
sub_3:Test (Best Model) - Loss: 0.6537 - Accuracy: 0.6786 - F1: 0.6648
sub_7:Test (Best Model) - Loss: 0.6714 - Accuracy: 0.6190 - F1: 0.6190
sub_9:Test (Best Model) - Loss: 0.6181 - Accuracy: 0.8333 - F1: 0.8299
sub_8:Test (Best Model) - Loss: 0.5933 - Accuracy: 0.8690 - F1: 0.8675
sub_11:Test (Best Model) - Loss: 0.5983 - Accuracy: 0.8690 - F1: 0.8675
sub_12:Test (Best Model) - Loss: 0.6446 - Accuracy: 0.7500 - F1: 0.7439
sub_4:Test (Best Model) - Loss: 0.5865 - Accuracy: 0.9048 - F1: 0.9045
sub_10:Test (Best Model) - Loss: 0.6548 - Accuracy: 0.7738 - F1: 0.7730
sub_2:Test (Best Model) - Loss: 0.6119 - Accuracy: 0.8690 - F1: 0.8681
sub_14:Test (Best Model) - Loss: 0.6154 - Accuracy: 0.8452 - F1: 0.8442
sub_7:Test (Best Model) - Loss: 0.6833 - Accuracy: 0.5595 - F1: 0.5238
sub_6:Test (Best Model) - Loss: 0.6305 - Accuracy: 0.7738 - F1: 0.7616
sub_9:Test (Best Model) - Loss: 0.6565 - Accuracy: 0.7500 - F1: 0.7439
sub_3:Test (Best Model) - Loss: 0.6444 - Accuracy: 0.7500 - F1: 0.7483
sub_11:Test (Best Model) - Loss: 0.6050 - Accuracy: 0.9048 - F1: 0.9039
sub_5:Test (Best Model) - Loss: 0.6542 - Accuracy: 0.7024 - F1: 0.6951
sub_13:Test (Best Model) - Loss: 0.6457 - Accuracy: 0.7619 - F1: 0.7618
sub_8:Test (Best Model) - Loss: 0.5757 - Accuracy: 0.9167 - F1: 0.9161
sub_12:Test (Best Model) - Loss: 0.6551 - Accuracy: 0.6667 - F1: 0.6506
sub_14:Test (Best Model) - Loss: 0.6337 - Accuracy: 0.7381 - F1: 0.7282
sub_10:Test (Best Model) - Loss: 0.6149 - Accuracy: 0.8571 - F1: 0.8571
sub_7:Test (Best Model) - Loss: 0.6883 - Accuracy: 0.5000 - F1: 0.4759
sub_2:Test (Best Model) - Loss: 0.5690 - Accuracy: 0.9405 - F1: 0.9403
sub_4:Test (Best Model) - Loss: 0.6438 - Accuracy: 0.7500 - F1: 0.7483
sub_1:Test (Best Model) - Loss: 0.6358 - Accuracy: 0.8690 - F1: 0.8686
sub_3:Test (Best Model) - Loss: 0.6552 - Accuracy: 0.7262 - F1: 0.7252
sub_6:Test (Best Model) - Loss: 0.6297 - Accuracy: 0.8333 - F1: 0.8309
sub_13:Test (Best Model) - Loss: 0.6400 - Accuracy: 0.8214 - F1: 0.8183
sub_8:Test (Best Model) - Loss: 0.5582 - Accuracy: 0.9643 - F1: 0.9642
sub_5:Test (Best Model) - Loss: 0.6441 - Accuracy: 0.8095 - F1: 0.8085
sub_9:Test (Best Model) - Loss: 0.6243 - Accuracy: 0.9048 - F1: 0.9045
sub_14:Test (Best Model) - Loss: 0.6356 - Accuracy: 0.7976 - F1: 0.7941
sub_10:Test (Best Model) - Loss: 0.6290 - Accuracy: 0.7500 - F1: 0.7439
sub_12:Test (Best Model) - Loss: 0.6389 - Accuracy: 0.6548 - F1: 0.6400
sub_4:Test (Best Model) - Loss: 0.6309 - Accuracy: 0.8214 - F1: 0.8212
sub_1:Test (Best Model) - Loss: 0.6152 - Accuracy: 0.8810 - F1: 0.8799
sub_2:Test (Best Model) - Loss: 0.5646 - Accuracy: 0.9286 - F1: 0.9282
sub_5:Test (Best Model) - Loss: 0.6854 - Accuracy: 0.6071 - F1: 0.6026
sub_6:Test (Best Model) - Loss: 0.6774 - Accuracy: 0.6071 - F1: 0.6057
sub_11:Test (Best Model) - Loss: 0.5428 - Accuracy: 0.9167 - F1: 0.9164
sub_14:Test (Best Model) - Loss: 0.6107 - Accuracy: 0.8810 - F1: 0.8803
sub_9:Test (Best Model) - Loss: 0.6027 - Accuracy: 0.8571 - F1: 0.8558
sub_3:Test (Best Model) - Loss: 0.6307 - Accuracy: 0.8095 - F1: 0.8085
sub_8:Test (Best Model) - Loss: 0.5625 - Accuracy: 0.9286 - F1: 0.9284
sub_12:Test (Best Model) - Loss: 0.6716 - Accuracy: 0.5714 - F1: 0.5088
sub_10:Test (Best Model) - Loss: 0.6277 - Accuracy: 0.7143 - F1: 0.7035
sub_7:Test (Best Model) - Loss: 0.6629 - Accuracy: 0.5595 - F1: 0.4901
sub_5:Test (Best Model) - Loss: 0.6488 - Accuracy: 0.7381 - F1: 0.7379
sub_4:Test (Best Model) - Loss: 0.6173 - Accuracy: 0.8214 - F1: 0.8208
sub_12:Test (Best Model) - Loss: 0.7139 - Accuracy: 0.3095 - F1: 0.3091
sub_2:Test (Best Model) - Loss: 0.6267 - Accuracy: 0.7262 - F1: 0.7079
sub_1:Test (Best Model) - Loss: 0.6180 - Accuracy: 0.8810 - F1: 0.8803
sub_8:Test (Best Model) - Loss: 0.5832 - Accuracy: 0.8929 - F1: 0.8927
sub_7:Test (Best Model) - Loss: 0.6777 - Accuracy: 0.6190 - F1: 0.5962
sub_3:Test (Best Model) - Loss: 0.6912 - Accuracy: 0.5119 - F1: 0.4958
sub_5:Test (Best Model) - Loss: 0.6946 - Accuracy: 0.4881 - F1: 0.4863
sub_13:Test (Best Model) - Loss: 0.6282 - Accuracy: 0.7500 - F1: 0.7471
sub_11:Test (Best Model) - Loss: 0.6213 - Accuracy: 0.8452 - F1: 0.8414
sub_10:Test (Best Model) - Loss: 0.6624 - Accuracy: 0.7143 - F1: 0.7136
sub_14:Test (Best Model) - Loss: 0.6323 - Accuracy: 0.8333 - F1: 0.8318
sub_6:Test (Best Model) - Loss: 0.6474 - Accuracy: 0.7500 - F1: 0.7456
sub_12:Test (Best Model) - Loss: 0.6172 - Accuracy: 0.8333 - F1: 0.8299
sub_9:Test (Best Model) - Loss: 0.6310 - Accuracy: 0.7738 - F1: 0.7722
sub_13:Test (Best Model) - Loss: 0.6473 - Accuracy: 0.7857 - F1: 0.7852
sub_1:Test (Best Model) - Loss: 0.6382 - Accuracy: 0.7619 - F1: 0.7614
sub_2:Test (Best Model) - Loss: 0.6000 - Accuracy: 0.9167 - F1: 0.9161
sub_8:Test (Best Model) - Loss: 0.6152 - Accuracy: 0.9524 - F1: 0.9523
sub_4:Test (Best Model) - Loss: 0.6248 - Accuracy: 0.8333 - F1: 0.8309
sub_10:Test (Best Model) - Loss: 0.6474 - Accuracy: 0.7619 - F1: 0.7569
sub_5:Test (Best Model) - Loss: 0.6451 - Accuracy: 0.7738 - F1: 0.7664
sub_6:Test (Best Model) - Loss: 0.6980 - Accuracy: 0.4405 - F1: 0.4103
sub_11:Test (Best Model) - Loss: 0.5770 - Accuracy: 0.9405 - F1: 0.9403
sub_3:Test (Best Model) - Loss: 0.6298 - Accuracy: 0.8452 - F1: 0.8450
sub_14:Test (Best Model) - Loss: 0.6472 - Accuracy: 0.5952 - F1: 0.5446
sub_4:Test (Best Model) - Loss: 0.6736 - Accuracy: 0.7024 - F1: 0.7003
sub_7:Test (Best Model) - Loss: 0.6675 - Accuracy: 0.7738 - F1: 0.7730
sub_12:Test (Best Model) - Loss: 0.6397 - Accuracy: 0.7738 - F1: 0.7683
sub_8:Test (Best Model) - Loss: 0.6065 - Accuracy: 0.9048 - F1: 0.9045
sub_9:Test (Best Model) - Loss: 0.6396 - Accuracy: 0.7381 - F1: 0.7343
sub_2:Test (Best Model) - Loss: 0.6009 - Accuracy: 0.9286 - F1: 0.9286
sub_1:Test (Best Model) - Loss: 0.6707 - Accuracy: 0.6786 - F1: 0.6785
sub_4:Test (Best Model) - Loss: 0.6482 - Accuracy: 0.7738 - F1: 0.7735
sub_6:Test (Best Model) - Loss: 0.6895 - Accuracy: 0.4762 - F1: 0.4762
sub_7:Test (Best Model) - Loss: 0.6737 - Accuracy: 0.6190 - F1: 0.6156
sub_10:Test (Best Model) - Loss: 0.6491 - Accuracy: 0.6310 - F1: 0.5810
sub_5:Test (Best Model) - Loss: 0.6639 - Accuracy: 0.6786 - F1: 0.6785
sub_13:Test (Best Model) - Loss: 0.6210 - Accuracy: 0.8333 - F1: 0.8325
sub_11:Test (Best Model) - Loss: 0.6094 - Accuracy: 0.8929 - F1: 0.8921
sub_14:Test (Best Model) - Loss: 0.6581 - Accuracy: 0.5714 - F1: 0.5088
sub_3:Test (Best Model) - Loss: 0.6589 - Accuracy: 0.6786 - F1: 0.6730
sub_9:Test (Best Model) - Loss: 0.6592 - Accuracy: 0.6667 - F1: 0.6506
sub_1:Test (Best Model) - Loss: 0.6236 - Accuracy: 0.8452 - F1: 0.8450
sub_2:Test (Best Model) - Loss: 0.6333 - Accuracy: 0.7500 - F1: 0.7439
sub_8:Test (Best Model) - Loss: 0.5845 - Accuracy: 0.8810 - F1: 0.8792
sub_13:Test (Best Model) - Loss: 0.5680 - Accuracy: 0.9286 - F1: 0.9285
sub_12:Test (Best Model) - Loss: 0.6724 - Accuracy: 0.6429 - F1: 0.5982
sub_5:Test (Best Model) - Loss: 0.6489 - Accuracy: 0.7381 - F1: 0.7306
sub_4:Test (Best Model) - Loss: 0.6601 - Accuracy: 0.7738 - F1: 0.7738
sub_10:Test (Best Model) - Loss: 0.6508 - Accuracy: 0.7857 - F1: 0.7776
sub_6:Test (Best Model) - Loss: 0.6888 - Accuracy: 0.4405 - F1: 0.3951
sub_14:Test (Best Model) - Loss: 0.6720 - Accuracy: 0.5952 - F1: 0.5446
sub_11:Test (Best Model) - Loss: 0.5947 - Accuracy: 0.9524 - F1: 0.9523
sub_7:Test (Best Model) - Loss: 0.6805 - Accuracy: 0.5714 - F1: 0.5625
sub_2:Test (Best Model) - Loss: 0.6441 - Accuracy: 0.8095 - F1: 0.8085
sub_9:Test (Best Model) - Loss: 0.6617 - Accuracy: 0.6190 - F1: 0.5787
sub_1:Test (Best Model) - Loss: 0.6445 - Accuracy: 0.7143 - F1: 0.7102
sub_8:Test (Best Model) - Loss: 0.6186 - Accuracy: 0.8333 - F1: 0.8299
sub_5:Test (Best Model) - Loss: 0.6442 - Accuracy: 0.7381 - F1: 0.7357
sub_4:Test (Best Model) - Loss: 0.6326 - Accuracy: 0.8214 - F1: 0.8183
sub_6:Test (Best Model) - Loss: 0.6701 - Accuracy: 0.6429 - F1: 0.6214
sub_10:Test (Best Model) - Loss: 0.6391 - Accuracy: 0.8095 - F1: 0.8085
sub_1:Test (Best Model) - Loss: 0.6504 - Accuracy: 0.7857 - F1: 0.7796
sub_3:Test (Best Model) - Loss: 0.6667 - Accuracy: 0.6071 - F1: 0.5354
sub_14:Test (Best Model) - Loss: 0.6825 - Accuracy: 0.5238 - F1: 0.4167
sub_12:Test (Best Model) - Loss: 0.6141 - Accuracy: 0.8214 - F1: 0.8170
sub_13:Test (Best Model) - Loss: 0.5493 - Accuracy: 0.9405 - F1: 0.9405
sub_9:Test (Best Model) - Loss: 0.6598 - Accuracy: 0.5714 - F1: 0.5333
sub_5:Test (Best Model) - Loss: 0.6750 - Accuracy: 0.6071 - F1: 0.5753
sub_7:Test (Best Model) - Loss: 0.6565 - Accuracy: 0.7857 - F1: 0.7838
sub_2:Test (Best Model) - Loss: 0.5514 - Accuracy: 0.8810 - F1: 0.8809
sub_8:Test (Best Model) - Loss: 0.6078 - Accuracy: 0.8810 - F1: 0.8807
sub_11:Test (Best Model) - Loss: 0.6101 - Accuracy: 0.8452 - F1: 0.8452
sub_4:Test (Best Model) - Loss: 0.6702 - Accuracy: 0.6071 - F1: 0.6003
sub_1:Test (Best Model) - Loss: 0.6661 - Accuracy: 0.6429 - F1: 0.6420
sub_10:Test (Best Model) - Loss: 0.6534 - Accuracy: 0.5714 - F1: 0.4750
sub_14:Test (Best Model) - Loss: 0.6751 - Accuracy: 0.4881 - F1: 0.4074
sub_6:Test (Best Model) - Loss: 0.6573 - Accuracy: 0.5952 - F1: 0.5446
sub_12:Test (Best Model) - Loss: 0.5720 - Accuracy: 0.7976 - F1: 0.7890
sub_1:Test (Best Model) - Loss: 0.6538 - Accuracy: 0.7738 - F1: 0.7735
sub_13:Test (Best Model) - Loss: 0.6431 - Accuracy: 0.8095 - F1: 0.8085
sub_2:Test (Best Model) - Loss: 0.6045 - Accuracy: 0.7857 - F1: 0.7826
sub_8:Test (Best Model) - Loss: 0.5882 - Accuracy: 0.8929 - F1: 0.8928
sub_3:Test (Best Model) - Loss: 0.6436 - Accuracy: 0.6905 - F1: 0.6630
sub_6:Test (Best Model) - Loss: 0.6869 - Accuracy: 0.5476 - F1: 0.4590
sub_7:Test (Best Model) - Loss: 0.6640 - Accuracy: 0.6905 - F1: 0.6903
sub_4:Test (Best Model) - Loss: 0.6269 - Accuracy: 0.8095 - F1: 0.8085
sub_9:Test (Best Model) - Loss: 0.6439 - Accuracy: 0.7262 - F1: 0.7172
sub_11:Test (Best Model) - Loss: 0.6094 - Accuracy: 0.9167 - F1: 0.9166
sub_3:Test (Best Model) - Loss: 0.6656 - Accuracy: 0.5595 - F1: 0.5518
sub_7:Test (Best Model) - Loss: 0.6666 - Accuracy: 0.6190 - F1: 0.6136
sub_13:Test (Best Model) - Loss: 0.5886 - Accuracy: 0.8452 - F1: 0.8442
sub_9:Test (Best Model) - Loss: 0.6018 - Accuracy: 0.8214 - F1: 0.8183
sub_11:Test (Best Model) - Loss: 0.6217 - Accuracy: 0.8452 - F1: 0.8450
sub_13:Test (Best Model) - Loss: 0.5675 - Accuracy: 0.9524 - F1: 0.9524
sub_11:Test (Best Model) - Loss: 0.6132 - Accuracy: 0.7857 - F1: 0.7838

=== Summary Results ===

acc: 75.13 ± 7.99
F1: 74.01 ± 8.58
acc-in: 82.45 ± 8.27
F1-in: 82.22 ± 8.46
